СПОСОБ И УСТРОЙСТВО ДЛЯ ОБРАБОТКИ ДАННЫХ О ПОЛЯРИЗАЦИИ ЧУВСТВИТЕЛЬНОЙ К ПОЛЯРИЗАЦИИ ОПТИЧЕСКОЙ КОГЕРЕНТНОЙ ТОМОГРАФИИ

Группа изобретений относится к медицине и может быть использована для обработки данных о поляризации в поляризационно-чувствительной оптической когерентной томографии. Группа изобретений представлена способом, устройством и постоянным машиночитаемым носителем. Обнаруживают свет датчиком обнаружения. Свет получен путем расщепления комбинированного света с использованием расщепителя поляризованного луча. Комбинированный свет получен путем комбинирования отраженного света от измеряемого образца, облучаемого измерительным светом, и опорного света, соответствующего измерительному свету. Получают множество наборов элементов данных о поляризации с помощью блока получения, получаемых из обнаруженного света. Преобразуют множество наборов элементов данных о поляризации в представление в векторной форме с помощью блока преобразования, включающее в себя информацию в отношении отставания и ориентации оси. Вычисляют средние значения множества наборов преобразованных элементов данных о поляризации с помощью ...

КЛАССИФИКАЦИЯ ИЗОБРАЖЕНИЯ НА ОСНОВЕ СЕГМЕНТАЦИИ ИЗОБРАЖЕНИЯ

... 1. Система (600) базы данных, содержащая систему (100) для классификации данных изображения на основе модели для адаптирования к объекту в данных изображения, причем система содержит: ! - блок (110) сегментации для сегментирования данных изображения путем адаптирования модели к объекту в данных изображения; и ! - блок (120) классификации для присвоения класса данным изображения на основе модели, адаптированной к объекту в данных изображения, таким образом, классифицируя данные изображения, ! и при этом блок (120) классификации содержит блок (122) атрибутов для вычисления значения атрибута модели на основе модели, адаптированной к объекту в данных изображения, и при этом присвоенный класс основан на вычисленном значении атрибута; ! и при этом, когда класс данных изображения и запись данных в базе данных являются идентичными или удовлетворяют определенному условию, запись данных может быть извлечена как запись данных, соответствующая изображению. ! 2. Система (600) базы данных по п.1, в которой ...

ОПРЕДЕЛЕНИЕ РАССТОЯНИЯ ДО ОБЪЕКТА ПО ИЗОБРАЖЕНИЮ

... 1. Устройство для определения расстояния до объекта сцены, причем устройство содержит:устройство (101) захвата изображений, имеющее кодированную апертуру и датчик изображений, причем датчик изображений расположен вне фокальной плоскости для объекта сцены;приемник (103) для приема первого изображения сцены от датчика изображений устройства (101) захвата изображений;обнаружитель (105) для обнаружения, по меньшей мере, двух объектов изображения в изображении, соответствующем теневым изображениям объекта сцены, возникающим как следствие различных отверстий кодированной апертуры в ответ на оптическую характеристику объекта сцены, причем оптическая характеристика является характеристикой излучения объекта в направлении устройства (101) захвата изображений; иблок (107) оценки расстояния для определения расстояния до объекта сцены в ответ на смещение в изображении, по меньшей мере, двух объектов изображения, причем упомянутое устройство отличается тем, что дополнительно содержит:источник (1101) ...

Bildverarbeitungsverfahren, Programm, ophthalmologische Vorrichtung und choroidales Blutgefäßbild-Erzeugungsverfahren

Die vorliegende Erfindung ermöglicht es, zu unterbinden, dass Retina-Blutgefäße einen Effekt auf eine Analyse von choroidalen Blutgefäßen haben.Bilddaten für ein erstes Augenhintergrundbild (das heißt ein R-Augenhintergrundbild) und ein zweites Augenhintergrundbild (das heißt ein G-Augenhintergrundbild) werden eingelesen und es werden Retina-Blutgefäße aus dem zweiten Augenhintergrundbild extrahiert. Die Retina-Blutgefäße werden dann aus dem ersten Augenhintergrundbild entfernt und choroidale Blutgefäße werden im ersten Augenhintergrundbild verstärkt, in welchem die choroidalen Blutgefäße relativ prominenter erscheinen. Als Ergebnis wird ein choroidales Blutgefäßbild erhalten, in welchem die choroidalen Blutgefäße verstärkt erscheinen.

Optical coherence tomography measuring apparatus

Improvements in or relating to image processing

Method of identifying anomalies in images

Optical image measuring device

Provided is an optical image measuring device which has a high lateral resolution and is capable of obtaining a generally sharp image. The optical image measuring device according to an embodiment comprises an optical system, an image formation unit, a control unit and a synthetic tomographic image formation unit. The optical system includes a scanning unit which changes an irradiation position of a signal light upon an object and an in-focus position changing unit which changes an in-focus position of the signal light. The optical system detects interference light between return light of each signal light from the object and reference light. The image formation unit forms a tomographic image on the basis of the detection result of a plurality of beams of the interference light that correspond to a plurality of irradiation positions of the signal light. The control unit changes the in-focus position and repetitively irradiates the plurality of irradiation positions with the signal light ...

Improvements in and relating to imaging of the eye

Improvements in and relating to imaging of the eye

A method of determining a measurement of at least one cell type in an eye, comprising: obtaining a map of the cell type in the eye which may be in 2D or 3D and may be a cell type density or distribution map, obtaining a representation of the retina of the eye and matching the eye cell type map to the representation of the retina of the eye. A region of interest is then defined on the representation of the retina of the eye and its size calculated. The matched eye cell type map and the size of the region of interest are then used to determine a measure of the cell type in the region of interest of the retina of the eye.

Ocular assessment

Image processing apparatus and image processing method

To provide pathological support for users to effectively perform follow up on diseases, using polarization information obtained from polarization-sensitive tomographic images. An image processing apparatus includes a positioning unit (195) configured to position multiple polarization-sensitive tomographic images corresponding to multiple tomographic luminance images, based on the plurality of tomographic luminance images obtained by photographing an object at different times; and a comparing unit (196) configured to compare the plurality of polarization-sensitive tomographic images which are positioned.

Systems and methods for obtaining information about the face and eyes of a subject

A computer-implemented method and an apparatus for obtaining information about the face of a subject, the method comprising illuminating the face of the subject 101 and capturing one or more images 102 of the face during each of a plurality of time periods. Then for each time period carrying out the steps of: using the images to form a respective three-dimensional skin model of the skin of the subject 103 and obtaining eye data indicative of the position of at least a portion of an eye of the subject during the time period 104. Having completed the steps for each time period, the eye data for the time periods is converted to a common reference frame using the respective skin models 108 and from the converted eye data an eye model comprising an estimate of the position of the centre of eye rotation CER of the eye of the subject is obtained 109. Typically, such an eye model is obtained for each of the subject's eyes. The eye model is used in a process for designing an item of eyewear such ...

Medical Image Analysis Using Neural Networks

Image acquisition apparatus

Image acquisition apparatus

Image acquisition apparatus

BEREICHERWEITERNDES SYSTEM AND SPACE FILTER

PROCEDURE FOR SEIZING A CHARACTERISTIC AT LEAST ONE ARTICLE

EYE PURSUIT LIGHTING

PROCEDURE AND SYSTEM FOR FILTERING A RED EYE PHENOMENON FROM A DIGITAL PICTURE

Ophthalmic device

There is provided a method of controlling an ophthalmic device having a first retinal image acquisition module operable to image an imaging region of a retina and an illumination module operable to concurrently illuminate an illumination region of the retina, the imaging region and the illumination region having a predetermined positional relationship to one another, the method comprises: controlling (S10) the first retinal image acquisition module to acquire a reference retinal image by imaging a reference imaging area of the retina; designating (S20) a target in the reference retinal image; controlling (S30) the first retinal image acquisition module to acquire a current retinal image of an initial imaging region within the reference imaging area; controlling (S40) the first retinal image acquisition module to move its imaging region of the retina from the initial imaging region to a destination imaging region using the target and at least a portion of the reference retinal image, and ...

Ophthalmic device

There is provided a method of controlling an ophthalmic device having a first retinal image acquisition module operable to image an imaging region of a retina and an illumination module operable to concurrently illuminate an illumination region of the retina, the imaging region and the illumination region having a predetermined positional relationship to one another, the method comprises: controlling (S10) the first retinal image acquisition module to acquire a reference retinal image by imaging a reference imaging area of the retina; designating (S20) a target in the reference retinal image; controlling (S30) the first retinal image acquisition module to acquire a current retinal image of an initial imaging region within the reference imaging area; controlling (S40) the first retinal image acquisition module to move its imaging region of the retina from the initial imaging region to a destination imaging region using the target and at least a portion of the reference retinal image, and ...

Shaking image for registration verification

A method and system are described that allow a user to verify a registration proposal during an image-guided ophthalmic surgery. The system configured to perform the method has a processor and a non-transitory computer-readable medium accessible to the processor containing instructions executable by the processor to perform the method.

Optical apparatus and associated devices for biometric identification and health status determination

The present disclosure provides techniques and apparatus for capturing an image of a person's retina fundus, identifying the person, accessing various electronic records (including health records) or accounts or devices associated with the person, determining the person's predisposition to certain diseases, and/or diagnosing health issues of the person. Some embodiments provide imaging apparatus having one or more imaging devices for capturing one or more images of a person' s eye(s). Imaging apparatus described herein may include electronics for analyzing and/or exchanging captured image and/or health data with other devices. In accordance with various embodiments, imaging apparatus described herein may be alternatively or additionally configured for biometric identification and/or health status determination techniques, as described herein.

METHOD AND SYSTEM FOR TRANSFORMING ADAPTIVELY VISUAL CONTENTS ACCORDING TO USER'S SYMPTOM CHARACTERISTICS OF LOW VISION IMPAIRMENT AND USER'S PRESENTATION PREFERENCES

Ophthalmologic photographing device

A reflected beam from the eyeground (1a) is divided into a left-right pair of beams by a two-hole aperture (31) disposed at the conjugate position of an anterior eye part (1b) of an eye (1) to be examined. A left-right pair of eyeground images having a parallax are formed from the divided beams at the position of a photographing mask (43) as an intermediate image. The optical path of the pair of eyeground images formed as the intermediate image is split by a pair of optical path split lenses (51, 52) disposed at a position substantially conjugate with the two-hole aperture, and one of the eyeground images is re-formed on one half of the imaging surface (53a) of an imaging element (53) and the other one of the eyeground images is re-formed separately on the other half of the imaging surface. According to the structure like this, it is possible to effectively obtain two eyeground images for three-dimensional viewing, without using a prism for splitting the optical path.

Resolution enhancement of OCT images during vitreoretinal surgery

Resolution enhancement of OCT images during ophthalmic surgery may be performed with an OCT scanning controller that interfaces to an OCT scanner used with a surgical microscope. Real-time OCT images may be acquired by the OCT scanner, while previously acquired high resolution OCT images are accessed by the OCT scanning controller. The high resolution OCT images may be morphed based on the real-time OCT images to match a deformation of the eye. The morphed high resolution OCT images may be displayed during surgery.

Methods and systems for ocular imaging, diagnosis and prognosis

Abstract Embodiments of the invention involve combining data representative of the eye obtained from multiple modalities into a virtual model of the eye. The multiple modalities indicate anatomical, physiological, and/or functional features of the eye. The data from different modalities is registered in order tocombine the data intothevirtual model. Further embodiments involve analysingeye data, for example in the form of the virtual model, using neural networks to obtain insights about medical conditions of the eye, for example the diagnosis or prognosis of conditions, and/or predicting how the eye will respond to certain treatments. WO 2020/055272 PCT/NZ2019/050121 25-/ -5 -10 -10 x Inferior/superior y = Temporal/nasal ...

Detection of pathologies in ocular images

Abstract 5 A computer-implemented method of searching for a region (410) indicative of a pathology in an image (400) of a portion of an eye acquired by an ocular imaging system (420), the method comprising: receiving (S10) image data defining the image; searching (S12) for the region in the image by processing the received image data using a learning algorithm; and in case a region in the image that is indicative of the pathology is found: 10 determining (S14) a location of the region in the image; generating (S16) an instruction for an eye measurement apparatus to measure a functional response of the eye to light stimulation to generate measurement data, using a reference point based on the determined location for setting a location of the measurement on the portion of the eye; and receiving (S18) the measurement data from the eye measurement apparatus. Fig. 3 ...

RANGE EXTENDING SYSTEM AND SPATIAL FILTER

A range of a wavefront sensor (36) is extended by focusing collimated light onto a lenslet array (33), an output creating a grid formed by edges of the lenslets (34) and a reference spot in the members of the grid. Each reference spot has a known relationship to the grid member and a centroid. A relationship between the reference centroids is determined. Next a wavefront emanating from an eye is focused onto the lenslet array (33), with the output from the lenslet array (33) forming the grid and aberrated eye spots thereon, each eye spot having a centroid. A relationship between the eye spot centroids is determined. One known relationship between one reference centroid and the centroid of one eye spot is identified. Finally, at least some of the remaining relationships between the reference centroids and the eye spot centroids are determined. The determined relationships provide a measure indicative of the eye aberration.

FAST FOCUS ASSESSMENT SYSTEM AND METHOD FOR IMAGING

An imaging apparatus which can be used to capture high-quality iris images for identification of a person. The iris imager as in the figure comprises a camera (105), a cold mirror (120), a lens (110), an illuminator (130), and a focus assessment processor. The imager has sensors and indicators which assist a user in aligning and focusing the device. The imager also automatically captures the image when proper positioning is achieved. The focus assessment processor accesses the image and applies certain measurement routines to assess the focus. The output of the focus assessment processor is used to control an indicator. A template representative of the iris features is extracted and then compared to a database of previously stored templates to identify the person.

OPHTHALMIC DEVICE

There is provided a method of controlling an ophthalmic device having a first retinal image acquisition module operable to image an imaging region of a retina and an illumination module operable to concurrently illuminate an illumination region of the retina, the imaging region and the illumination region having a predetermined positional relationship to one another, the method comprises: controlling (S10) the first retinal image acquisition module to acquire a reference retinal image by imaging a reference imaging area of the retina; designating (S20) a target in the reference retinal image; controlling (S30) the first retinal image acquisition module to acquire a current retinal image of an initial imaging region within the reference imaging area; controlling (S40) the first retinal image acquisition module to move its imaging region of the retina from the initial imaging region to a destination imaging region using the target and at least a portion of the reference retinal image, and ...

METHOD FOR AUTOMATIC SHAPE QUANTIFICATION OF AN OPTIC NERVE HEAD

The invention relates to a method and a computer program for automatic shape quantification of an optic nerve head from three-dimensional image data (1) acquired with optical coherence tomography, comprising the steps of: a) Providing (100) three-dimensional image data (1) of the retina, the image data comprising at least a portion of the optic nerve head, wherein the image data comprises pixels with associated pixel values; b) In the three-dimensional image data (1) identifying (200, 300) anatomic portions of the optic nerve head, the anatomic portions comprising a retinal pigment epithelium (RPE) portion (3) and an inner limiting membrane (ILM) portion (2); c) Determining an RPE polygon mesh (30) for a lower boundary of the retinal pigment epithelium portion (3), wherein the RPE polygon mesh (30) extends along the lower boundary of the retinal pigment epithelium portion (3); d) Determining an ILM polygon mesh (20) for the inner limiting membrane portion (2), wherein the ILM polygon mesh ...

FAST AND AUTOMATED SEGMENTATION OF LAYERED IMAGE WITH HEURISTIC GRAPH SEARCH

A method of processing an ophthalmic image includes: taking an image of an ophthalmic region involving an ophthalmic layer by an imaging system; constructing an image graph, comprising nodes connected by links and detected image data by an image processor; and performing a heuristic graph-search for a path on the image graph that corresponds to an image of the ophthalmic layer by assigning at least one of link-costs to links of the image graph and node-costs to nodes of the image graph; assigning heuristic-costs to at least one of the nodes and the links; creating extended paths by extending a selected path with extension links; determining path-costs of the extended paths by combining heuristic costs and at least one of link-costs and node-costs assigned to the extension-links; and selecting the extended path with the smallest path-cost.

IRIS RECOGNITION METHODS AND SYSTEMS BASED ON AN IRIS STOCHASTIC TEXTURE MODEL

The present disclosure describes systems and methods of using iris data for authentication.A biometric encoder may translate an image of the iris into a rectangular representation of the iris. The rectangular representation may include a plurality of rows corresponding to a plurality of annular portions of the iris. The biometric encoder may extract an intensity profile from at least one of the plurality of rows, the intensity profile modeled as a stochastic process. The biometric encoder may obtain a stationary stochastic component of the intensity profile by removing a non-stationary stochastic component from the intensity profile. The biometric encoder may remove at least a noise component from the stationary component using auto-regressive based modeling, to produce at least a non-linear background signal, and may combine the non-stationary component and the at least the non-linear background signal, to produce a biometric template for authenticating the person.

OCULAR SURFACE INTERFEROMETRY (OSI) DEVICES, SYSTEMS, AND METHODS FOR IMAGING, PROCESSING, AND/OR DISPLAYING AN OCULAR TEAR FILM AND/OR MEASURING OCULAR TEAR FILM LAYER THICKNESS(ES)

EVALUATING AND REDUCING MYOPIAGENIC EFFECTS OF ELECTRONIC DISPLAYS

Techniques for evaluating and reducing myopiagenic effects of electronic displays are disclosed. The invention includes a method for generating at least one corrected frame based on the level of stimulation of cones in a viewer's eye, a method for providing at least one corrected frame, wherein one or more red-hued pixels in the corrected frame has a reduced degree of red saturation compared to the corresponding pixel in an uncorrected frame, and a method for displaying a page of a text on a mobile device, wherein the text and background colors have a reduced myopiagenic effect.

RESOLUTION ENHANCEMENT OF OCT IMAGES DURING VITREORETINAL SURGERY

Resolution enhancement of OCT images during ophthalmic surgery may be performed with an OCT scanning controller that interfaces to an OCT scanner used with a surgical microscope. Real-time OCT images may be acquired by the OCT scanner, while previously acquired high resolution OCT images are accessed by the OCT scanning controller. The high resolution OCT images may be morphed based on the real-time OCT images to match a deformation of the eye. The morphed high resolution OCT images may be displayed during surgery.

AUTOMATED FINE ADJUSTMENT OF AN OPHTHALMIC SURGERY SUPPORT

The present disclosure provides a system for automated fine adjustment of an ophthalmic surgery support in which an eye tracking system detects a detectable position of an eye. The direction and distance the support must be adjusted for the eye to be centered may be determined based on the detectable position. A control signal is generated and transmitted to a control device that adjusts the position of the support to center the eye. The disclosure further provides a method for automated fine adjustment of a support, which includes detecting a detectable position of an eye, determining whether the eye is centered in relation to the center of the detection field of an eye tracking system based on the detectable position, determining a direction and a distance the detectable position must be adjusted to be centered, and generating and transmitting a control signal to adjust the position of the support.

SYSTEMS AND METHODS FOR DETECTION OF OCULAR DISEASE

Disclosed herein are computer systems for, in part, image processing. Also disclosed herein are systems for processing ocular images of multiple imaging modalities to detect ocular diseases. Also disclosed herein are method comprising systems as described herein.

OPTICAL COHERENCE TOMOGRAPHY CROSS VIEW IMAGING

An optical coherence tomography (OCT) system and method for cross view imaging using at least two B-scan images transformed and coupled to each other at an angle to generate a cross view image.

IMAGE ANALYSIS USING MACHINE LEARNING AND HUMAN COMPUTATION

Methods, systems, and computer readable media for analyzing an image using machine learning and human computation. A method for analyzing an image includes providing, via multiple instances of an interactive application (334) for analysis of the image, multiple instances, respectively, of the image and receiving, via the interactive application, data (240) from results of analyses of the image including multiple sets of user inputs from the analyses of the multiple instances of the image, respectively. The multiple sets of user inputs are from multiple users, respectively and the multiple users are associated with the multiple instances of the interactive application, respectively. The method further includes processing the received data to identify areas of interest within the image based on the multiple sets of user inputs and analyzing the image using a machine learning algorithm (245) to identify structures in the image based on the identified areas of interest within the image.

DETECTION OF PATHOLOGIES IN OCULAR IMAGES

A computer-implemented method of searching for a region (410) indicative of a pathology in an image (400) of a portion of an eye acquired by an ocular imaging system (420), the method comprising: receiving (S10) image data defining the image; searching (S12) for the region in the image by processing the received image data using a learning algorithm; and in case a region in the image that is indicative of the pathology is found: determining (S14) a location of the region in the image; generating (S16) an instruction for an eye measurement apparatus to perform a measurement on the portion of the eye to generate measurement data, using a reference point based on the determined location for setting a location of the measurement on the portion of the eye; and receiving (S18) the measurement data from the eye measurement apparatus.

TRACKING TORSIONAL EYE ORIENTATION AND POSITION

Methods and systems for tracking a position and torsional orientation of a patient's eye. In one embodiment, the present invention provides methods and software for registering a first image of an eye (56, 64) with a second image of an eye (66). In another embodiment, the present invention provides methods and software for tracking a torsional movement of the eye. In a particular usage, the present invention tracks the torsional cyclorotation and translational movement of a patient's eye so as to improve the delivery of a laser energy (12, 76) to the patient's cornea.

METHOD AND SYSTEM TO DETECT OPHTHALMIC TISSUE STRUCTURE AND PATHOLOGIES

A method to determine an ophthalmic tissue structure comprises measuring image data for a range of depths corresponding to a target point in an eye with an axial scanner with a probe; determining an image information by an imaging processor from the image data; identifying a tissue pathology corresponding to the target point by the processor from the image information; and signaling a user by a user indicator based on the identified tissue pathology. A corresponding apparatus comprises an axial scanner with a probe to measure image data for a range of depths corresponding to a target point in an eye; a processor to determine an image information from the image data, and to identify a tissue pathology corresponding to the target point from the image information; and a user indicator to signal a user based on the identified tissue pathology.

Method for the analysis of image data representing a three-dimensional volume of biological tissue

A method and device for determining an effective medical image

Method and system for transforming adaptively visual contents according to user's symptom characteristics of low vision impairment and user's presentation preferences

Eyelid detection device and program

An eyelid detection device which on the basis of a primary differential value and a secondary differential value of a gradation change in the vertical direction within the boundary of the eyelid in an image of an eye, shifts the secondary differential value in an upper direction by just one-fourth of the period of the frequency of the gradation change within the boundary of the eyelid, combines the primary differential value and the secondary differential value, and calculates a top eyelid feature amount. The eyelid detection device detects the boundary between the eye and the top eyelid on the basis of the peak point in the vertical direction of the top eyelid feature amount that was calculated. Hereby, the boundary between the eyelid and eye can be correctly detected even when there is make-up on the eyelid.

OCT angiography data analysis and visualization

For assessment of corneal health status change apparatus and method

For identifying diabetic retinopathy artificial neural network device and system device

Method and system for extracting clear image frame from recorded fundus video

... 本发明涉及一种从所录制的眼底视频中提取清晰图像帧的方法和系统，通过将视频文件每帧图像的YUV化，再对每个像素点的特征值进行计算，并寻找到具有最大有效反差平均值的某一帧图像，最终将该帧图像输出。本发明中的方法和系统能应用于各种眼底图像采集设备。采集者录制一段采集过程中摄像装置直接捕获到的视频，如：在预备阶段尝试对准采集设备入瞳与被采集者瞳孔，采集中数次对准并成功短暂或持续捕获到高质量的眼底图像，采集间隙中与被采集者协调调整拍摄角度等，及完成采集后的过渡阶段。采集者无需对视频进行人工剪辑或者对软件参数进行设置，就能在软件处理后获得高质量的眼底图像，并经由人工进一步筛选出具有代表性的部分，以供临床诊断。 ...

DEVICE FOR DETECTING STATE OF THE CORNEA OF THE EYE AND ASSOCIATED METHOD

L'invention concerne un dispositif (1) de détection d'un état de la cornée (3) de l'œil (5) comprenant une unité (11) d'imagerie de contraste à granularité laser, présentant • une source (13) de rayonnement électromagnétique cohérent destiné à éclairer la cornée (3) de l'œil (5), • un détecteur (15) d'au moins une image de chatoiement diffusée par la cornée (3) de l'œil (5), • une unité (17) de traitement de l'image de chatoiement configurée pour établir un histogramme normalisé de l'image de chatoiement, et pour déterminer l'ordre de la loi Gamma permettant d'extrapoler l'histogramme normalisé.

IMAGE PROCESSING APPARATUS, IMAGE PROCESSING METHOD, TOMOGRAM CAPTURING APPARATUS, AND PROGRAM RECORDING MEDIUM

Health Care System and Method through Iridology

IMAGE PROCESSING METHOD FOR PLANNING OF ORTHODONTIC TREATMENT, APPARATUS, AND RECORDING MEDIUM THEREOF

전자 디스플레이의 근시 발생 효과 평가 및 감소

... 전자 디스플레이들의 근시 발생 효과를 평가하고 감소시키는 기술들이 개시되어 있다.

SYSTEM AND METHOD FOR IDENTIFYING EYE CONDITIONS

IMAGE PROCESSING APPARATUS, CONTROL METHOD THEREOF, AND COMPUTER PROGRAM

IMAGE PROCESSING APPARATUS, CONTROL METHOD THEREOF, AND COMPUTER PROGRAM

SYSTEM AND METHOD FOR BLOOD VESSEL SCANNING

Method and apparatus for reducing myopiagenic effect of electronic displays

Techniques for evaluating and reducing myopiagenic effects of electronic displays are disclosed.

METHOD OF SEARCHING FOR PARAMETERIZED CONTOURS FOR COMPARING IRISES

The subject of the invention is a method for detecting contours for comparing irises. It comprises a step (301, 401, 402) of selecting N candidate contours of circular shape (403, 404, 405, 406) by applying a technique for searching for a circle on an image of edges of an iris (300). It also comprises a step (302, 504, 505, 506, 507) of optimizing the shape and the position of the N candidate contours, the optimized candidate contours being determined by using parametric models, a set of parameters being determined by candidate contour and minimizing a quantity of energy E (C). The method comprises furthermore a step (303, 604) of selecting the best optimized candidate contour (605).

IMAGE PROCESSING APPARATUS, IMAGE PROCESSING METHOD, PROGRAM, AND PROGRAM RECORDING MEDIUM

An image processing unit obtains information indicating continuity of tomograms of a subject's eye, and a determining unit determines the image capturing state of the subject's eye on the basis of the information obtained by the image processing unit.

SYSTEM AND METHOD FOR ANALYZING IMAGING DATA

A method of analyzing a stream of imaging data is disclosed. The method comprises: for each picture-element of the data, associating a vector of features indicative of temporal intensity variation relative to baseline intensity, thereby providing a plurality of vectors. The method further comprises clustering the picture-elements according to the vectors, thereby providing a plurality of clusters, and identifying different compartments in the vasculature based on the clusters.

AUTOMATIC DETECTION OF RED LESIONS IN DIGITAL COLOR FUNDUS PHOTOGRAPHS

Disclosed is an automated method (100) which can detect images containing red-lesions. First, each image is preprocessed (200); next, candidate objects that may represent red-lesions are extracted (300); and in the final stage (400) the probability for each candidate to represent a red-lesion is estimated using a classifier and a large set of specifically designed features.

METHOD AND APPARATUS FOR GENERATION OR EDITING OF LAYER DELINEATIONS

Methods are disclosed for the generation and editing of layer delineations within three-dimensional tomography scans. Cross sections of a subject are generated and presented to an operator, who has the ability to edit layer delineations within the cross section, or determine parameters used to generate new cross sections. By guiding an operator through a set of displayed cross sections, the methods can allow for a more rapid, efficient, and error-free segmentation of the subject. The cross sections can be nonplanar in shape or planar and non-axis-aligned. The cross sections can be restricted to exclude one or more user-defined regions of the subject, or to include only one or more user-defined regions of the subject. The cross sections can be localized to a point-of-interest. Iterative implementations of the methods can be used to arrive at a segmentation deemed satisfactory by the user.

INFANT MONITORING SYSTEM

A monitoring system includes a sensor, a processing block and an alert generator. The sensor is used to generate images of an infant. The processing block processes one or more of the images and identifies a condition with respect to the infant. Then alert generator causes generation of an alert signal if the identified condition warrants external notification. In an embodiment, the sensor is a 3D camera, and the 3D camera, the processing block and the alert generator are part of a unit placed in the vicinity of the infant. The monitoring system further includes microphones and motion sensors to enable detection of sounds and movement.

GAZE DETERMINATION MACHINE LEARNING SYSTEM HAVING ADAPTIVE WEIGHTING OF INPUTS

Machine learning systems and methods that determine gaze direction by using face orientation information, such as facial landmarks, to modify eye direction information determined from images of the subject's eyes. System inputs include eye crops of the eyes of the subject, as well as face orientation information such as facial landmarks of the subject's face in the input image. Facial orientation information, or facial landmark information, is used to determine a coarse prediction of gaze direction as well as to learn a context vector of features describing subject face pose. The context vector is then used to adaptively re-weight the eye direction features determined from the eye crops. The re-weighted features are then combined with the coarse gaze prediction to determine gaze direction.

Image processing apparatus, ophthalmologic imaging apparatus, image processing method, and storage medium

An image processing apparatus includes an identification unit configured to identify periodicity of a fundus image obtained by capturing an image of a fundus of an eye, and an information acquisition unit configured to acquire information indicating an imaging state of photoreceptor cells in the fundus image based on the periodicity.

SPECTACLE WEARING PARAMETER MEASUREMENT DEVICE, SPECTALE WEARING PARAMETER MEASUREMENT PROGRAM, AND POSITION SPECIFYING METHOD

A spectacle wearing parameter measurement device used in measurement of a spectacle wearing parameter of a subject who is to wear a spectacle frame, the spectacle wearing parameter measurement device includes: an information processing unit that acquires each of a first image as a face image of the subject in a spectacle-frame wearing state and a second image as a face image in a spectacle-frame non-wearing state and prepares a third image obtained by associating the first image and the second image; a display screen unit that displays the third image prepared by the information processing unit; an operation unit that specifies a measurement reference point of the spectacle wearing parameter on the third image displayed on the display screen unit; and a measurement computation section that calculates the spectacle wearing parameter by using data of the specified measurement reference point. 1. A spectacle wearing parameter measurement device used in measurement of a spectacle wearing parameter of a subject who is to wear a spectacle frame , the spectacle wearing parameter measurement device comprising:an information processing unit that acquires each of a first image as a face image of the subject in a spectacle-frame wearing state and a second image as a face image in a spectacle-frame non-wearing state and prepares a third image obtained by associating the first image and the second image;a display screen unit that displays the third image prepared by the information processing unit;an operation unit that specifies a measurement reference point of the spectacle wearing parameter on the third image displayed on the display screen unit; anda computation unit that calculates the spectacle wearing parameter by using data of the specified measurement reference point.2. The spectacle wearing parameter measurement device according to claim 1 , whereinthe third image is a synthetic image obtained by synthesizing the first image in the spectacle-frame wearing state and the ...

Automatic detection of red lesions in digital color fundus photographs

Disclosed is an automated method which can detect images containing red lesions. First, each image is preprocessed; next, candidate objects that may represent red-lesions are extracted; and in the final stage the probability for each candidate to represent a red-lesion is estimated using a classifier and a large set of specifically designed features.

System for measuring curved surfaces

A device and method for fitting contact lenses to a patient that matches the anterior curve of the lens to the measured cornea of the patient improving the optical performance of the lens on the eye.

Method and systems for measuring interpupillary distance

The proposed innovation provides methods and systems for measuring the interpupillary distance. The proposed innovation provides a fitting pad (102) having two detection points (104 and 106). The fitting pad is placed on the forehead of the user and an image is captured. The image is uploaded and pupil distance calculator software locates the fitting detection points and calculates the distance in pixels of the left and right X, Y coordinates. The software creates an image scale by dividing the pixel counts between the detection points. The software automatically locates the X, Y coordinates between the center of the left and right pupils and calculates the distance in pixels. The resulting pixel distance divided by the image scale provides the interpupillary distance in millimeter. In embodiments, segment height is calculated based upon an image imported by the user and the combined scaled images of the user and the frame.

Evaluating and reducing myopiagenic effects of electronic displays

A system includes a full-color electronic display, an eye-tracking module arranged to track an eye of a viewer of the display during operation of the system, at least one programmable processor, and a machine-readable medium storing instructions that, when executed by the at least one programmable processor to perform operations, including: (i) assessing uncorrected image data with one or more image frames, including determining an initial color of pixels in an image frame; (ii) assessing, based on data from the eye-tracking module, a location on the display where the viewer's eye is looking; (iii) modifying a color of red pixels from its initial color to a modified red color based on the location of the pixel relative to the location on the display where the viewer's eye is looking and the initial color of the pixel; and (iv) displaying, on the display, the image frames in which the one or more pixels have the modified color and other pixels have their initial color.

OPTIC NEUROPATHY DETECTION WITH THREE-DIMENSIONAL OPTICAL COHERENCE TOMOGRAPHY

Based on optical coherence tomography (OCT) imaging of a portion of an eye, a mask of an anatomical feature is derived. Using the mask as a reference, a scan path is determined that is at least partially fitted to and/or partially enclosing the mask. OCT scan data corresponding to the scan path is acquired and analyzed to detect optic neuropathies.

Ophthalmologic apparatus and control method for the same

A fundus imaging apparatus for acquiring a fundus image; and a measurement unit that extracts a characteristic image of a fundus image from a first fundus image captured by the fundus imaging apparatus, detects the characteristic image from a second fundus image that is different from the fundus image, and measures a position change in the fundus images from coordinates of the extracted characteristic image and the detected characteristic image in the respective fundus images, wherein a region in which the characteristic image is detected from the second fundus image is determined so that a region searched for the characteristic image from the first image includes the extracted characteristic image and is broader than a range of movement of the characteristic image resulting from movements of the eye ball within measurement time.

Method for the autonomous image segmentation of flow systems

Disclosed herein is a method that comprises obtaining an image of a network section through which flow occurs; where the flow is selected from a group consisting of fluid, electrons, protons, neutrons and holes; subjecting the image to a low pass filter to increase contrast in portions of the network sections; computing a local mean of visible light intensity at each pixel that is present in the image; calculating a visible light intensity difference between each pixel and the local mean of visible light intensity and producing a differentiated image using this calculation; creating a base image of the differentiated image; where the base image comprises a hand segmented gold standard dataset; removing objects below a minimum threshold size from the base image; and retaining the remaining objects if they approximate the line or spine.

Image processing method and system for edge detection and laser eye surgery system incorporating the same

A method of imaging an object includes obtaining an image data set from a raster scan. The image data set has a plurality of data points, each data point having an associated location and intensity; generating a reduced data set by selectively removing one or more data points from the image data set based upon an assigned probability of retaining the one or more data points in the data set, the assigned probability being a function of the intensity of a data point; generating a triangulation graph as a planar subdivision having faces that are triangles, the vertices of which are the data points and the edges of which are adjacent vertices; and segmenting the triangulated data set by finding a path with lowest cost between that vertex and every other vertex, wherein the cost is a function of the respective intensity of the vertices.

BIOMETRIC IDENTIFICATION SYSTEMS AND ASSOCIATED DEVICES

The present disclosure provides techniques and apparatus for capturing an image of a person's retina fundus, identifying the person, accessing various electronic records (including health records) or accounts or devices associated with the person, determining the person's predisposition to certain diseases, and/or diagnosing health issues of the person. Some embodiments provide imaging apparatus having one or more imaging devices for capturing one or more images of a person's eye(s). Imaging apparatus described herein may include electronics for analyzing and/or exchanging captured image and/or health data with other devices. In accordance with various embodiments, imaging apparatus described herein may be alternatively or additionally configured for biometric identification and/or health status determination techniques, as described herein.

Image analysis system and/or method

Among other things, a method is disclosed comprising: receiving image data representing an image; processing the data to generate orientation information; processing the data using the orientation information to measure a quantity called local phase in a direction perpendicular to the orientation of a putative vessel; using the phase measurements from three collinear image locations or from two locations to detect the centerline of a symmetric image structure, such as a blood vessel, and to locate a center-point defined by the intersection of the centerline with the line created by the measurement locations.

Reconstruction of three dimensional model of an object from surface or slice scans compensating for motion blur

Techniques for creating a three dimensional model of an object and eliminate artifacts due to object motion. Such techniques are applied to line scans and slice scans of an object.

DEVICE FOR SCREENING CONVERGENCE INSUFFICIENCY AND RELATED COMPUTER IMPLEMENTED METHODS

A device is for screening a person for CI and may include a binocular viewer, a display adjacent the binocular viewer, and a processor and associated memory cooperating with the display. The processor may be configured to display on the display a first visual stimulus and a second visual stimulus, cause, in alternating fashion, convergent movement and divergent movement in the first visual stimulus and the second visual stimulus along a visual stimulus path, determine respective centroid positions of the second eye and the first eye during the convergent and divergent movement of the first visual stimulus and the second visual stimulus, and calculate an IPD, and compare the IPD with the visual stimulus path to obtain a dynamic IPD, the dynamic IPD serving as an indicator for whether the person has CI.

IMAGE PROCESSING APPARATUS, CONTROL METHOD THEREOF, AND COMPUTER PROGRAM

The present invention an image processing apparatus, which processes an image of a tomogram obtained by capturing an image of an eye to be examined by a tomography apparatus, comprises, layer candidate detection means for detecting layer candidates of a retina of the eye to be examined from the tomogram, artifact region determination means for determining an artifact region in the tomogram based on image features obtained using the layer candidates, and image correction means for correcting intensities in the artifact region based on a determination result of the artifact region determination means and image features in the region.

OPTIMAL, USER-FRIENDLY, OBJECT BACKROUND SEPARATION

A method of identifying an object of interest can comprise obtaining first samples of an intensity distribution of one or more object of interest, obtaining second samples of an intensity distribution of confounder objects, transforming the first and second samples into an appropriate first space, performing dimension reduction on the transformed first and second samples, whereby the dimension reduction of the transformed first and second samples generates an object detector, transforming one or more of the digital images into the first space, performing dimension reduction on the transformed digital images, whereby the dimension reduction of the transformed digital images generates one or more reduced images, classifying one or more pixels of the one or more reduced images based on a comparison with the object detector, and identifying one or more objects of interest from the classified pixels.

Ophthalmic apparatus

An ophthalmic apparatus includes a control unit configured to control a scanning unit so that scanning lines of a first field and scanning lines of a second field are alternately arranged in a direction crossing the scanning lines, and a detection unit configured to, in a case where one of first front images of the first field is selected as a reference image, detect movement of the subject's eye using information indicating a position gap between the reference image and the first front images, and detect the movement of the subject's eye using information indicating a position gap between the reference image and second front images of the second field and information indicating a difference in position between the first field and the second field.

Image processing apparatus, control method thereof and computer program

One aspect of embodiments of the present invention relates to an image processing apparatus which specifies one of boundary positions of retina layers in a fundus image showing a retina tomosynthesis, sets a distance transfer function for converting the distance from the specified boundary position to a parameter expressing opacity such that the peak position of the opacity is set to a predetermined position in the retina, sets a luminance transfer function for converting a luminance value of the fundus image to the parameter expressing opacity, and generates a translucent display image by calculating the opacity of respective positions of the tomosynthesis using the distance transfer function and the luminance transfer function, and by volume rendering.

USING REAL-TIME IMAGES FOR AUGMENTED-REALITY VISUALIZATION OF AN OPHTHALMOLOGY SURGICAL TOOL

A system includes a processor and a display. The processor is configured to: (a) receive, from a camera inserted into an eye of a patient, at least an optical image of at least a region-of-interest (ROI) of the eye, (b) receive, from a position tracking system (PTS), a position signal indicative of a position of a medical instrument treating the eye, (c) register the optical image and the PTS in a common coordinate system, and (d) estimate the position of the medical instrument in the optical image. The display is configured to visualize at least the ROI and the medical instrument.

IMAGE RECOGNITION METHOD, STORAGE MEDIUM AND COMPUTER DEVICE

This application provides an image recognition method, a storage medium, and a computer device. The method includes: obtaining a to-be-recognized image; preprocessing the to-be-recognized image, to obtain a preprocessed image; obtaining, through a first submodel in a machine learning model, a first image feature corresponding to the to-be-recognized image, and obtaining, through a second submodel in the machine learning model, a second image feature corresponding to the preprocessed image; and determining, according to the first image feature and the second image feature, a first probability that the to-be-recognized image belongs to a classification category corresponding to the machine learning model. It may be seen that, the solutions provided by this application can improve recognition efficiency and accuracy.

Face-image processing apparatus

A multivalue image of the face input by a CCD camera 2 is stored in a multivalue-image memory 3. A multivalue-image characteristic extracting means 23 extracts a pixel of interest from the stored multivalue face image in accordance with distribution of relative brightness of the brightness of the pixel of interest and those of pixels adjacent to the pixel of interest. The extracted pixel of interest is stored in a binarized-image memory 5. The stored pixel of interest is used to extract an eye region. In accordance with the extracted eye region, an opening/closing determining means 7 determines opening/closing of the eyes.

OCT image processing

An apparatus for rendering optical coherence tomography, OCT, retinal image data, acquired by an OCT scanner scanning a retina of an eye over a range of scan locations, wherein each scan location is associated with a respective coordinate in a first coordinate system, and each pixel of the rendered OCT retinal image data is associated with a respective coordinate in a second coordinate system different from the first coordinate system. The apparatus comprises a communication module arranged to receive the OCT retinal image data, and a coordinate-determining module arranged to determine values of coordinates in the second coordinate system of pixels in the received OCT retinal image using a transformation from coordinates in the first to second coordinate system. The apparatus further comprises an interpolation module arranged to interpolate between values of pixels at the determined values to calculate values of the pixels of the rendered OCT retinal image data.

DETECTION TARGET POSITIONING DEVICE, DETECTION TARGET POSITIONING METHOD, AND SIGHT TRACKING DEVICE

Disclosed is a detection target positioning method and device. The method comprises: acquiring an original image and pre-processing the original image to obtain a gradation of each pixel in a target gradation image corresponding to a target region including a detection target; calculating first gradation sets corresponding to rows of pixels of the target gradation image and second gradation sets corresponding to columns of pixels of the target gradation image; and determining rows of two ends of the detection target in a column direction according to the first gradation sets, determining columns of two ends of the detection target in a row direction according to the second gradation sets, and determining a center of the detection target according to the row of two ends of the detection target in the column direction and the columns of two ends of the detection target in the row direction.

Method and apparatus for obtaining an image of an ocular feature

A method, apparatus and software containing instructions for obtaining an image of an ocular feature are disclosed. The disclosed embodiments include at least the steps of defining one or more selection criteria which are related to an ocular feature of interest. The selection criteria may relate to an ocular feature type, an ocular feature location, or other relevant matters. The method further includes capturing a stream of sequential ocular images and autonomously scoring some or all ocular images according to the selection criteria. Images that score above a defined score threshold may be selected as individual images more likely to include a suitable representation of the ocular feature of interest than other individual ocular images.

Identifying retinal layer boundaries

Methods for automatically identifying retinal boundaries from a reflectance image are disclosed. An example of the method includes identifying a reflectance image of the retina of a subject; generating a gradient map of the reflectance image, the gradient map representing dark-to-light or light-to-dark reflectance differentials between adjacent pixel pairs in the reflectance image; generating a guidance point array corresponding to a retinal layer boundary depicted in the reflectance image using the gradient map; generating multiple candidate paths estimating the retinal layer boundary in the reflectance image by performing a guided bidirectional graph search on the reflectance image using the guidance point array; and identifying the retinal layer boundary by merging two or more of the multiple candidate paths.

Systems and methods for providing surface contrast to display images for micro-surgical applications

Systems and methods for providing surface contrast to display images for micro-surgical applications are disclosed. According to an aspect, an imaging system includes an OCT apparatus configured to capture OCT data of an eye. The OCT image data can include depth-resolved images of reflected light intensity over a period of time. The imaging system also includes a controller configured to determine movement of the eye relative to the OCT imaging field-of-view. The controller may also determine a location within the imaged portion of the eye which tracks with the eye movement. Further, the controller may apply a color gradient to render OCT images of the eye based on a position relative to the determined location of the eye tracking location. The controller may also control a display to display the OCT images with the applied color gradient.

ANALYSIS AND VISUALIZATION OF OCT ANGIOGRAPHY DATA

EYE STATE ASSESSMENT METHOD AND ELECTRONIC DEVICE

The disclosure provides an eye state assessment method and an electronic device. The method includes: obtaining an optic disc image area from a first fundus photography and generating multiple optic cup-to-disc ratio assessment results by multiple first models based on the optic disc image area; obtaining a first assessment result of an eye based on the optic cup-to-disc ratio assessment results; performing multiple data augmentation operations on the first fundus photography to generate multiple second fundus photographies; generating multiple retinal nerve fiber layer (RNFL) defect assessment results by multiple second models based on the second fundus photographies; obtaining a second assessment result of the eye based on the RNFL defect assessment results; and obtaining an optic nerve assessment result of the eye based on the first assessment result and the second assessment result.

Fundus observation apparatus

The fundus observation apparatus 1 has a function to form tomographic images and 3-dimensional images of a fundus Ef by scanning signal light LS as well as a function to form a moving image (observation image K) of a fundus Ef during OCT measurement. Furthermore, the fundus observation apparatus 1 includes an x-correction part 231 and a y-correction part 232 for correcting a position in the fundus surface direction of the 3-dimensional image based on the observation image K, and a z-correction part 233 for correcting the position in the fundus depth direction of a 3-dimensional image, based on a tomographic image Gi of the fundus Ef based on the detection results of interference light LC of separately scanned signal light LS and reference light LR.

Image processing apparatus, image processing method, image processing system, and computer readable memory

An image processing apparatus includes an extraction unit configured to extract a structure of a tested eye from an OCT image obtained by optical coherence tomography, an extraction unit configured to extract a structure of the tested eye from an eyeground image obtained by a scanning laser ophthalmoscope or a fundus camera, a calculation unit configured to calculate a reliability degree of the extraction for each of the extracted structures, and a display control unit configured to display the extracted structures superimposed on a image of eyeground according to the calculated reliability.

Systems and methods for multilayer imaging and retinal injury analysis

Systems and methods are provided for imaging an eye and identifying retinal or subretinal features that may be indicative of pathologies such as macular degeneration and traumatic brain injury. An infrared or near-infrared image of an eye is interdependently smoothed and segmented and attributes of the image are determined. The attributes are indicative of retinal or subretinal features.

Image processing apparatus and method

An image processing apparatus which processes a plurality of tomograms obtained by acquiring, along a direction crossing at a right angle a section along the thickness direction of a retina, a plurality of tomograms each including the section, detects a layer structure in the retina from image information of respective lines of the tomograms along the thickness direction, and appends structure information to the respective lines based on the layer structures detected for the respective lines. The image processing apparatus maps the structure information of the respective lines of the plurality of tomograms onto a plane crossing the thickness direction at a right angle, thereby generating a two-dimensional image based on the structure information.

Image processing apparatus for processing tomographic image of subject's eye, imaging system, method for processing image, and recording medium

An image processing apparatus includes a detection unit configured to detect layers on the retina based on tomographic images of the retina, an acquisition unit configured to acquire a region having a larger curvature of the boundary surface between the retina and the corpus vitreum than a threshold value, and a determination unit configured to determine an optic disc of the retina based on the optical disc including a region where a specific layer is not detected by the detection unit and the region acquired by the acquisition unit.

method and system of determining a grade of nuclear cataract

A method for determining a grade of nuclear cataract in a test image. The method includes: (1a) defining a contour of a lens structure in the test image, the defined contour of the lens structure comprising a segment around a boundary of a nucleus of the lens structure; (1b) extracting features from the test image based on the defined contour of the lens structure in the test image; and (1c) determining the grade of nuclear cataract in the test image based on the extracted features and a grading model.

Ophthalmic photographing apparatus

An ophthalmic photographing apparatus includes: an interference optical system having a light source, a splitter for splitting light from the light source into measurement light traveling toward an examinee's eye and reference light, and an optical detector for receiving combined light of the measurement light reflected by the examinee's eye and the reference light; an optical scanner arranged in an optical path of the measurement light to scan a photographing region of the examinee's eye with the measurement light; a controller for obtaining a tomographic image of the photographing region by controlling the optical scanner and processing an output signal from the optical detector; and an image processor for obtaining a combined tomographic image by combining a plurality of tomographic images corresponding to a plurality of different incident angles.

Image Analysis System and Related Methods and Computer Program Products

Methods are provided including receiving a plurality of images from at least one image acquisition system; selecting at least a portion of a set of images for analysis using at least one attribute of image metadata; selecting at least one method for deriving quantitative information from the at least a portion of the set of images; processing the selected at least a portion of the set of images with the selected at least one method for deriving quantitative information; associating the derived quantitative information with the at least a portion of the set of images via a data structure; selecting at least one method for aggregating at least a portion of a set of derived quantitative information into a reduced set of results; and generating at least one report to represent the reduced set of results for one of an individual image and the set of images as a pool.

Image processing apparatus and method

In a tomographic image photographing apparatus, a deformation of a volume image is corrected accurately even if an object to be inspected moves when the volume image is acquired. An image processing apparatus acquires a tomographic image of the object to be inspected from combined light beams of return light beams, which is obtained by irradiating the object to be inspected with a plurality of measuring light beams, and corresponding reference light beams. In the image processing apparatus, a photographing unit obtains a tomographic image of a fundus with the plurality of measuring light beams, and a detection unit detects a retina layer from the tomographic image. Based on the detected retina layer, a fundus shape is estimated. Based on the estimated fundus shape, a positional deviation between tomographic images is corrected.

Non-linear projections of 3-d medical imaging data

The present invention improves projection displays of volume data. Using the Minimum Intensity Projection (MinIP), fluid filled regions or other regions of hyporeflective tissue are displayed. By limiting the projection to partial volumes within the volume, differences in the scattering intensity within specific regions are isolated. In this way, hyperreflectivity of weakly scattering tissue can be assessed.

Iris deblurring method based on global and local iris image statistics

A method of identifying a living being includes using a camera to capture a blurred visual image of an iris of the living being. The blurred visual image is digitally unblurred based on a distribution of eye image gradients in an empirically-collected sample of eye images and characteristics of pupil region. The unblurred image is processed to determine an identity of the living being.

Optical coherence tomographic apparatus, control method for optical coherence tomographic apparatus and storage medium

An optical coherence tomographic apparatus includes a unit configured to perform tracking of an eye to be examined based on a plurality of images of the eye which are obtained at different times, and a control unit configured to control the unit which performs the tracking in a case where a plurality of tomographic images of the eye are obtained.

Calculating Conjunctival Redness

The present application includes methods, systems and computer readable storage devices for determining a color score for at least a portion of a biological tissue. The subject matter of the application is embodied in a method that includes obtaining a digital image of the biological tissue, and receiving a selection of a portion of the image as an evaluation area. The method also includes determining for each of a plurality of pixels within the evaluation area, a plurality of color components that are based on a Cartesian color space, and determining, from the color components, a hue value in a polar coordinate based color space. The method further includes determining a color value based on the hue value for each of the plurality of pixels, and assigning a color score to the evaluation area based on an average of the color values of the plurality of pixels.

Corneal graft evaluation based on optical coherence tomography image

An OCT image of an eye which has been subject to a DSAEK corneal transplant, in which a Descement's membrane in the cornea has been replaced by a graft, is processed to identify the outline of the graft. The process includes the steps of: computationally extracting the boundary of the cornea including the graft; computationally detecting the corners of the graft; computationally extracting points on the boundary between the graft and the original cornea; and computationally fitting the points on the boundary between the graft and the original cornea smoothly into a curve. The outline of the graft is then displayed. A graft profile may be generated, indicating the thickness of the graft at each point along its length.

Method and Systems for Measuring Interpupillary Distance

The proposed innovation provides methods and systems for measuring the interpupillary distance. The proposed innovation provides a fitting pad ( 102 ) having two detection points ( 104 and 106 ). The fitting pad is placed on the forehead of the user and an image is captured. The image is uploaded and pupil distance calculator software locates the fitting detection points and calculates the distance in pixels of the left and right X, Y coordinates. The software creates an image scale by dividing the pixel counts between the detection points. The software automatically locates the X, Y coordinates between the center of the left and right pupils and calculates the distance in pixels. The resulting pixel distance divided by the image scale provides the interpupillary distance in millimeter. In embodiments, segment height is calculated based upon an image imported by the user and the combined scaled images of the user and the frame.

Method and apparatus for multi-level eye registration

A method for performing multi-level eye registration comprising: obtaining a first initial reference eye image by a first diagnostic device and defining a reference coordinate system; obtaining a second eye image by a surgery device, said second eye image being obtained in a pre-surgery phase before the surgery has started; performing a first registration between said first eye image and said second eye image to obtain a first registration result; obtaining a third eye image by said surgery device, said third eye image being obtained after surgery has started; performing a second registration between said second eye image and said third eye image to obtain a second registration result; combining said first and second registration results to obtain a combined registration result to thereby obtain a registration between said initial reference eye image obtained by said diagnostic device and said third eye image obtained by said surgery device after surgery has started.

Method for correcting user's gaze direction in image, machine-readable storage medium and communication terminal

A method and mobile terminal for correcting a gaze of a user in an image includes setting eye outer points that define an eye region of the user in an original image, transforming the set eye outer points to a predetermined reference camera gaze direction, and transforming the eye region of the original image based on the transformed eye outer points.

Image processing apparatus, image processing method, and program

For appropriately obtaining the tomographic image and the layer thickness map are provided in a short period of time regardless of involuntary eye movement, when the tomographic image is to be obtained in a specific scan pattern, a 3D tomographic image is first obtained by 3D scan, and then a tomographic image of a desired part is extracted from the image in accordance with the specific scan pattern. Further, based on the obtained 3D tomographic image, a sector for layer thickness map display, a main scanning line, and a sub-scanning line, which are displayed on a fundus image, are set movable, and tomographic images taken along both the scanning lines after the movement are obtained. The sector having a center corresponding to the intersection between those scanning lines and the layer thickness map are recalculated and displayed so as to follow the intersection.

Quantification of local circulation with oct angiography

Impaired intraocular blood flow within vascular beds in the human eye is associated with certain ocular diseases including, for example, glaucoma, diabetic retinopathy and age-related macular degeneration. A reliable method to quantify blood flow in the various intraocular vascular beds could provide insight into the vascular component of ocular disease pathophysiology. Using ultrahigh-speed optical coherence tomography (OCT), a new 3D angiography algorithm called split-spectrum amplitude-decorrelation angiography (SSADA) was developed for imaging microcirculation within different intraocular regions. A method to quantify SSADA results was developed and used to detect perfusion changes in early stage ocular disease. Associated embodiments relating to methods for quantitatively measuring blood flow at various intraocular vasculature sites, systems for practicing such methods, and use of such methods and systems for diagnosing certain ocular diseases are herein described.

Ophthalmic diagnosis support apparatus and ophthalmic diagnosis support method

Provided is an ophthalmic diagnosis support apparatus which enables an operator to easily acquire a tomographic image suitable for detailed observation of a candidate lesion without spending time and effort to search for the candidate lesion. The ophthalmic diagnosis support apparatus includes an acquiring unit for acquiring a wide-range image of a fundus, a candidate lesion detection unit for detecting the candidate lesion on the fundus by analyzing the wide-range image, a calculating unit for determining a degree of abnormality of the candidate lesion based on a result of the detection of the candidate lesion, and an acquiring position setting unit for setting an acquiring position of the tomographic image of the fundus based on the degree of abnormality of the candidate lesion.

SYSTEMS, METHODS, AND DEVICES FOR OPTICAL COHERENCE TOMOGRAPHY MULTIPLE ENFACE ANGIOGRAPHY AVERAGING

The disclosure herein provides methods, systems, and devices for improving optical coherence tomography machine outputs through multiple enface optical coherence tomography angiography averaging techniques. The embodiments disclosed herein can be utilized in ophthalmology for employing optical coherence tomography (OCT) for in vivo visualization of blood vessels and the flow of blood in an eye of a patient, which is also known generally as optical coherence tomography angiography (OCTA). The embodiments disclosed herein can use linear registration, affine registration and/or elastic registration to align a plurality of optical coherence tomography angiography images or videos at corresponding superficial vascular layers having well-defined features or landmarks, and to apply the same linear registration, affine registration and/or elastic registration settings and/or data to corresponding deeper tissue layers, such as the choriocapillaris, which generally do not have well-defined features or landmarks, in order to align a plurality of corresponding deeper tissue layers for the purpose of averaging the images or video to produce a clearer and more accurate image or video of the tissue structure at deeper tissue layers. 1. (canceled)2. A system for obtaining and processing images of a biological material , the system comprising:one or more computer readable storage devices configured to store a plurality of computer executable instructions; and access or obtain a plurality of OCT images generated from an OCT scanner;', 'generate, from the plurality of OCT images, a plurality of enface images of one or more superficial layers of the biological material and a plurality of enface images of one or more deep layers;', 'divide each of the plurality of enface images of the one or more superficial layers and each of the plurality of enface images of the one or more deep layers into a plurality of sectors;', 'apply one or more image registration techniques to each of the ...

AUTOMATICALLY DETECTING EYE TYPE IN RETINAL FUNDUS IMAGES

A computer-implemented method includes obtaining an image of a retinal fundus. A plurality of features is extracted from the image of the retinal fundus. The plurality of features includes at least one feature based on anatomical domain knowledge of the retinal fundus and at least one response of a pre-trained deep convolutional neural network to at least a portion of the image of the retinal fundus. The retinal fundus is determined to belong to a left eye or a right eye, based on an analysis of the plurality of features. 1. A computer-implemented method , comprising:cropping a region of interest from an image of a retinal fundus;passing the region of interest through a stack of N learned convolutional layers of a pre-trained deep convolutional neural network;discarding a response of an Nth layer of the N learned convolutional layers to the region of interest;applying principal component analysis on responses of an (N-1)th layer of the N learned convolutional layers to the region of interest to generate a set of principal components;extracting an unsupervised feature of the retinal fundus from the set of principal components; anddetermining whether the retinal fundus belongs to a left eye or a right eye, based on an analysis of a combination of the unsupervised feature and a supervised feature of the retinal fundus.2. The computer-implemented method of claim 1 , wherein the region of interest is centered on an optic disc depicted in the image of the retinal fundus.3. The computer-implemented method of claim 2 , wherein the Nth layer is trained for one thousand classes of a training dataset claim 2 , and the (N-1)th layer generates more than four thousand responses as potential unsupervised features.4. The computer-implemented method of claim 1 , wherein the determining is performed using a support vector machine that has been trained using a plurality of features including the unsupervised feature and a supervised feature of the retinal fundus.5. The computer- ...

OPHTHALMIC DIAGNOSIS SUPPORT APPARATUS AND OPHTHALMIC DIAGNOSIS SUPPORT METHOD

Provided is an ophthalmic diagnosis support apparatus which enables an operator to easily acquire a tomographic image suitable for detailed observation of a candidate lesion without spending time and effort to search for the candidate lesion. The ophthalmic diagnosis support apparatus includes an acquiring unit for acquiring a wide-range image of a fundus, a candidate lesion detection unit for detecting the candidate lesion on the fundus by analyzing the wide-range image, a calculating unit for determining a degree of abnormality of the candidate lesion based on a result of the detection of the candidate lesion, and an acquiring position setting unit for setting an acquiring position of the tomographic image of the fundus based on the degree of abnormality of the candidate lesion. 116-. (canceled)17. An ophthalmic apparatus comprising:an acquiring unit configured to acquire a volume image of a fundus;a candidate detecting unit configured to detect a candidate lesion in a retina by analyzing the volume image;a calculating unit configured to calculate a degree of abnormality of the candidate lesion based on a detection result for the candidate lesion;a first determining unit configured to determine coordinates of a first point corresponding to the detected candidate lesion in accordance with the calculated degree of abnormality;a characteristic region detecting unit configured to detect a characteristic region in the fundus by analyzing the volume image, the characteristic region including a macula lutea;a second determining unit configured to determine coordinates of a second point corresponding to the characteristic region detected by the characteristic region detecting unit anda setting unit configured to set a straight line corresponding to an imaging position to be used for acquiring a tomographic image based on the coordinates of the first point corresponding to the candidate lesion and the coordinates of the second point corresponding to the characteristic ...

IMAGE PROCESSING APPARATUS, IMAGE PROCESSING METHOD, AND PROGRAM

An image processing apparatus includes a calculation unit configured to calculate information indicating similarity among a plurality of tomographic images, and a generation unit configured to generate a tomographic image from the plurality of tomographic images based on the calculated information indicating similarity. 1calculation means configured to calculate information indicating similarity among a plurality of tomographic images; andgeneration means configured to generate a tomographic image from the plurality of tomographic images based on the calculated information indicating similarity.. An image processing apparatus comprising: This application is a Continuation of co-pending U.S. patent application Ser. No. 14/580,652 filed Dec. 23, 2014, which is a Continuation of U.S. application Ser. No. 13/702,705 (now U.S. Pat. No. 8,983,164), filed Dec. 7, 2012, which is a U.S. national stage application of International Patent Application No. PCT/JP2011/002995, filed May 30, 2011, which claims the priority benefit of Japanese Patent Application No. 2010-131257, filed Jun. 8, 2010. All of the above-named applications are hereby incorporated by reference herein in their entirety.The present invention relates to a technique for the enhancement of image quality of a tomographic image in an eye portion.A tomographic imaging apparatus for the eye portion such as an optical coherence tomography (hereinafter referred to as OCT) is usable to three-dimensionally observe a state inside a retinal layer. In recent years, the tomographic imaging apparatus has attracted attention because it is useful in accurately diagnosing disease.In an ophthalmologic diagnosis, there can be used a volume image for grasping the state of the entire retinal layer and a high image-quality two-dimensional tomographic image for grasping a layer which is not imaged on a low image-quality tomographic image. The volume image refers to aggregation of the two-dimensional tomographic images.The image ...

Pupillometry Systems, Methods, and Devices

Pupillometry systems for measuring pupillary characteristics of a patient are shown and described. The puillometry systems include at least one camera, and a computer system in data communication with the at least one camera, the computer system having a processor and a non-transitory computer-readable storage medium. The non-transitory computer-readable storage medium includes computer-readable instructions for collecting and time stamping the image data, processing the raw image data in such a way as to bring the images into conformance with standardized image parameters, identifying and measuring the one or more pupils in the image data, processing the image data to produce measurement data of change in the one or more pupillary characteristics, calculating a standardized output of measurement data for the one or more pupillary characteristics, and providing a mechanism to share or store this information with other users via a computer network. 2. The pupillometry system of claim 1 , wherein the adjustment of the image properties and/or adjustment of the criteria used to identify the pupil is based on measurements of the existing ambient illumination.4. The pupillometry system of claim 1 , further comprising a system in which the non-transitory computer-readable storage medium has instructions for adjusting the level of illumination from the radiation source.5. The pupillometry system of claim 4 , wherein the level of illumination is adjusted based on measurements of the existing ambient illumination.7. The pupillometry system of claim 1 , wherein the computer readable storage medium contains instructions for adjusting the criteria for identifying and measuring one or more pupils based on measured image properties that include one or more of the following in one or more color channels: image brightness claim 1 , image contrast claim 1 , minimum pixel values claim 1 , distribution of pixel values claim 1 , maximum pixel values claim 1 , either in the image as a ...

IMAGE PROCESSING APPARATUS, IMAGE PROCESSING METHOD, AND PROGRAM THEREFOR

Provided is an image processing apparatus configured to process an image of a fundus of an eye to accurately measure thicknesses of membranes that form a blood vessel wall of an eye. The image processing apparatus includes: an image acquiring unit configured to acquire an image of an eye; a vessel feature acquiring unit configured to acquire membrane candidate points that form an arbitrary wall of a blood vessel based on the acquired image; a cell identifying unit configured to identify a cell that forms the wall of the blood vessel based on the membrane candidate points; and a measuring position acquiring unit configured to identify a measuring position regarding the wall of the blood vessel based on a position of the identified cell. 1. An image processing apparatus , comprising:an image acquiring unit configured to acquire an image of an eye;a vessel feature acquiring unit configured to acquire membrane candidate points that form a wall of a blood vessel based on the acquired image;a cell identifying unit configured to identify a cell that forms the wall of the blood vessel based on the membrane candidate points; anda measuring position acquiring unit configured to identify a measuring position regarding the wall of the blood vessel based on a position of the identified cell.2. An image processing apparatus according to claim 1 , wherein the measuring position acquiring unit is further configured to identify the measuring position based on a distance from a predetermined position within the cell identified in at least one membrane.3. An image processing apparatus according to claim 1 , further comprising a measuring unit configured to calculate at least one of a membrane thickness claim 1 , a compound membrane thickness claim 1 , and a wall thickness of the blood vessel in the identified measuring position as a measurement value regarding the wall of the blood vessel.4. An image processing apparatus according to claim 3 , wherein the measuring unit is further ...

DIAGNOSTIC CLASSIFICATION OF CORNEAL SHAPE ABNORMALITIES

Disclosed are systems and methods for characterizing corneal shape abnormalities. These methods may be used to differentiate corneas having subclinical keratoconus from other conditions which cause distortion of corneal shape, including warpage of the cornea due to contact lens wear. Also disclosed is classification scheme to aid diagnosis of corneal conditions and thereby guide clinical decision making regarding patient treatment. This classification scheme is based on computed properties of corneal shape, is amenable to automation, and may be implemented in an integrated system or provided in the form of software encoded on a computer-readable medium. 1. A computer-based method of classifying corneal shape abnormalities , said method comprising:generating a corneal topography map of a subject's cornea;generating an epithelial thickness map of the subject's cornea;calculating an epithelial thickness pattern standard deviation (PSD) value based on the epithelial thickness map;calculating a warpage index based on the corneal topography map and the epithelial thickness map; andclassifying the subject's cornea using the epithelial PSD value and the warpage index.2. The method of claim 1 , wherein the corneal topography map is a mean curvature map of an anterior surface of the cornea.3. The method of claim 1 , wherein the epithelial thickness map is generated using optical coherence tomography.4. The method of claim 1 , further comprising:generating a pachymetry map of the subject's cornea; andcalculating an ectasia index based on the corneal topography map and the pachymetry map;wherein the classifying the subject's cornea comprises classifying the subject's cornea using the epithelial PSD value, the warpage index, and the ectasia index.5. The method of claim 4 , wherein the pachymetry map is generated using optical coherence tomography.6. The method of claim 4 , wherein the corneal topography map claim 4 , epithelial thickness map and pachymetry map are pattern ...

Augmented and virtual reality display systems and methods for determining optical prescriptions

Configurations are disclosed for a health system to be used in various healthcare applications, e.g., for patient diagnostics, monitoring, and/or therapy. The health system may comprise a light generation module to transmit light or an image to a user, one or more sensors to detect a physiological parameter of the user's body, including their eyes, and processing circuitry to analyze an input received in response to the presented images to determine one or more health conditions or defects.

Methods and systems for diagnosing binocular vision conditions

Configurations are disclosed for a health system to be used in various healthcare applications, e.g., for patient diagnostics, monitoring, and/or therapy. The health system may comprise a light generation module to transmit light or an image to a user, one or more sensors to detect a physiological parameter of the user's body, including their eyes, and processing circuitry to analyze an input received in response to the presented images to determine one or more health conditions or defects.

Methods and systems for diagnosing eyes using aberrometer

Configurations are disclosed for a health system to be used in various healthcare applications, e.g., for patient diagnostics, monitoring, and/or therapy. The health system may comprise a light generation module to transmit light or an image to a user, one or more sensors to detect a physiological parameter of the user's body, including their eyes, and processing circuitry to analyze an input received in response to the presented images to determine one or more health conditions or defects.

METHODS AND SYSTEMS FOR PERFORMING SLIT LAMP EXAMINATION

Configurations are disclosed for a health system to be used in various healthcare applications, e.g., for patient diagnostics, monitoring, and/or therapy. The health system may comprise a light generation module to transmit light or an image to a user, one or more sensors to detect a physiological parameter of the user's body, including their eyes, and processing circuitry to analyze an input received in response to the presented images to determine one or more health conditions or defects. 1. (canceled)2. A wearable augmented reality device comprising:an augmented reality head-mounted ophthalmic system comprising an augmented reality display platform configured to pass light from the world into an eye of a wearer wearing the head-mounted ophthalmic system;an optical source configured to project an illumination beam of light into the eye of the wearer to illuminate an anterior or posterior portion of the eye, a cross-sectional beam shape of the illumination beam configured such that a dimension of the cross-sectional beam shape along a superior-inferior direction of the eye is greater than a dimension of the cross-sectional beam shape along a nasal-temporal direction of the eye; andan imaging system configured to capture an image of the illuminated portion of the wearer's eye to perform a slit lamp examination to determine health of the eye.3. The device of claim 2 , wherein the optical source is configured to project the illumination beam onto a location on a surface of the eye at an angle with respect to a normal to the surface at the location claim 2 , wherein the angle is between about ±10-degrees and about ±90-degrees.4. The device of claim 3 , wherein the illumination beam is incident the location along an axis intersecting the eye and passing through the pupil.5. The device of claim 2 , wherein the illumination beam has a width along a temporal-nasal axis of the wearer's eye claim 2 , wherein the width is between about 25 microns and about 1.0 mm.6. The ...

METHODS AND SYSTEMS FOR DETECTING HEALTH CONDITIONS BY IMAGING PORTIONS OF THE EYE, INCLUDING THE FUNDUS

Configurations are disclosed for a health system to be used in various healthcare applications, e.g., for patient diagnostics, monitoring, and/or therapy. The health system may comprise a light generation module to transmit light or an image to a user, one or more sensors to detect a physiological parameter of the user's body, including their eyes, and processing circuitry to analyze an input received in response to the presented images to determine one or more health conditions or defects. 1. (canceled)2. A wearable augmented reality device comprising:an augmented reality head-mounted ophthalmic system comprising an augmented reality display platform configured to pass light from the world into an eye of a wearer wearing the head-mounted ophthalmic system;a light source configured to illuminate a portion of the wearer's eye; andan imaging system configured to capture an image of the illuminated portion of the wearer's eye,wherein the augmented reality head-mounted ophthalmic system is configured to monitor health of the wearer's eye and detect abnormalities of the eye based on the image.3. The device of claim 2 , wherein the light source is a variable focus light source configured to project a beam of light into the wearer's eyes and to focus the beam of light at varying depths in the wearer's eye.4. The device of claim 2 , wherein the display platform comprises a fiber scanning display claim 2 , wherein fiber scanning display is the light source claim 2 , wherein fiber scanning display is configured to project a beam of light of a particular focus to the portion of the wearer's eye.5. The device of claim 4 , wherein the fiber scanning display comprises damaging system claim 4 , wherein the fiber scanning display is configured to project the beam of light and to capture the image of the illuminated portion of the wearer's eye.6. The device of claim 5 , wherein the imaging system is an eye tracking camera.7. The device of claim 2 , further comprising an electronic ...

SYSTEMS AND METHODS FOR INTRAOCULAR LENS SELECTION

Systems and methods for intraocular lens selection include receiving, by one or more computing devices implementing a prediction engine, pre-operative multi-dimensional images of an eye; extracting, by the prediction engine, pre-operative measurements of the eye based on the pre-operative images; estimating, by the prediction engine using a prediction model based on a machine learning strategy, a post-operative position of an intraocular lens based on the extracted pre-operative measurements; selecting a power of the intraocular lens based on the estimated post-operative position of the intraocular lens; and selecting the intraocular lens based on the selected power. In some embodiments, the systems and methods further include receiving post-operative multi-dimensional images of the eye after implantation of the selected intraocular lens, extracting post-operative measurements of the eye, and updating the prediction model based on the pre-operative measurements and the post-operative measurements. 1. A method comprising:receiving, by one or more computing devices implementing a prediction engine, one or more pre-operative multi-dimensional images of an eye;extracting, by the prediction engine, one or more pre-operative measurements of the eye based on the one or more pre-operative images of the eye, wherein the one or more pre-operative measurements of the eye at least include an estimated position of the lens equator determined as an equator line between each of two intersection points of an anterior lens radius and a posterior lens radius;estimating, by the prediction engine using a first prediction model based on a machine learning strategy, a post-operative position of an intraocular lens based on the one or more extracted pre-operative measurements of the eye;selecting a power of the intraocular lens based on at least the estimated post-operative position of the intraocular lens; andselecting the intraocular lens based on at least the selected power.2. The ...

SYSTEM AND METHOD FOR DETERMINING THE POSITION AND ORIENTATION OF A TOOL TIP RELATIVE TO EYE TISSUE OF INTEREST

System and method for determining the position and orientation (P&O) of a tool-tip relative to an eye tissue of interest. The system includes and imaging and tracking module coupled with a processor. The imaging and tracking module at least includes an imager. The imager acquires at least one image of at least one tissue-reference-marker. The imaging and tracking module further determines information relating to the P&O of the tool. The processor determines the P&O of the tissue-reference-marker according to the acquired image of the tissue-reference-marker. The processor determines the P&O of the eye tissue of interest, according to the P&O of the tissue-reference-marker, and a predetermined relative P&O between the tissue-reference-marker and the eye tissue of interest. The processor also determines the P&O of a tool-tip according to a tool-marker and determines the relative P&O between the tool-tip and the eye tissue of interest. 1. A system for determining the position and orientation of a tool tip relative to an eye tissue of interest , the system comprising:an imaging and tracking module, said imaging and tracking module at least including an imager, said imager acquiring at least one image of at least one tissue reference marker, said at least one tissue reference marker being different from said eye tissue of interest, said imaging and tracking module further determining information relating to the position and orientation of said tool; anda processor coupled with said imaging and tracking module, said processor determining, continuously and in real-time, the position and orientation of said tissue reference marker according to the acquired at least one image of said tissue reference marker,said processor determining the position and orientation of said eye tissue of interest, continuously and in real-time, according to said position and orientation of said tissue reference marker, and a predetermined relative position and orientation between said tissue ...

IMAGE PROCESSING APPARATUS AND STORAGE MEDIUM

An image processing apparatus includes: an analyzer configured to process a plurality of examinee's eye images taken from a same examinee's eye, at least a part of the examinee's eye images being overlapped with each other, and output an analysis result of a cell of the examinee's eye for each of the examinee's eye images; and an instruction receiving unit configured to receive an instruction regarding a target to be analyzed by the analyzer in the plurality of examinee's eye images from an examiner, wherein the analyzer outputs the analysis results in which the instruction received by the instruction receiving unit is reflected for each of the plurality of examinee's eye images. 1. An image processing apparatus including:an analyzer configured to process a plurality of examinee's eye images taken from a same examinee's eye, at least a part of the examinee's eye images being overlapped with each other, and output an analysis result of a cell of the examinee's eye for each of the examinee's eye images; andan instruction receiving unit configured to receive an instruction regarding a target to be analyzed by the analyzer in the plurality of examinee's eye images from an examiner,wherein the analyzer outputs the analysis results in which the instruction received by the instruction receiving unit is reflected for each of the plurality of examinee's eye images.2. The image processing apparatus according to claim 1 , further including a display control unit configured to display one of the plurality of examinee's eye images on a display device claim 1 ,wherein the instruction receiving unit receives the instruction from the examiner via one examinee's eye image displayed by the display control unit, andin a case where the instruction is received by the instruction receiving unit, the analyzer outputs the analysis results in which the instruction is reflected for each of the plurality of examinee's eye images.3. The image processing apparatus according to claim 1 ,wherein ...

IMAGE PROCESSING APPARATUS AND IMAGE PROCESSING METHOD

The present invention relates to accurately determining a contour of a depolarizing region. 1. An image processing apparatus comprising:an extracting unit configured to extract a depolarizing region in a polarization-sensitive tomographic image of a subject's eye;a detecting unit configured to detect, in a tomographic intensity image of the subject's eye, a region corresponding to the extracted depolarizing region, the tomographic intensity image corresponding to the polarization-sensitive tomographic image;a calculating unit configured to calculate a size of the detected region; anda display control unit configured to cause a display unit to display the detected region superimposed on the tomographic intensity image and to cause the display unit to display the calculated size in a state of associating the calculated size with the detected region.2. The image processing apparatus according to claim 1 , wherein the detecting unit detects claim 1 , in the tomographic intensity image claim 1 , a position of the region corresponding to the extracted depolarizing region by using information about a position of the extracted depolarizing region in the polarization-sensitive tomographic image claim 1 ,wherein the detecting unit detects a contour of the region corresponding to the extracted depolarizing region by using information about the detected position and the tomographic intensity image.3. The image processing apparatus according to claim 1 , wherein the polarization-sensitive tomographic image and the tomographic intensity image are positionally associated with each other.4. The image processing apparatus according to claim 1 , further comprising a generating unit configured to split interference light of return light from the subject's eye irradiated with measuring light and reference light corresponding to the measuring light into a plurality of polarization components claim 1 , and generate the polarization-sensitive tomographic image and the tomographic ...

Robust Eye Tracking for Scanning Laser Ophthalmoscope

A system, apparatus, and method of obtaining an image of a fundus. Acquiring a reference image of the fundus at a first point in time. Acquiring a target image of the fundus at a second point in time. The target imaging area may overlap with the reference imaging area. An area of the target imaging area may be less than an area of the reference imaging area. Estimating movement of the fundus may be based upon at least the target image and the reference image. Acquiring a narrow field image of the fundus. An area of the narrow field imaging area may be less than the area of the target imaging area. A position of the narrow imaging area on the fundus may be adjusted based on the estimated movement of the fundus.

METHOD AND DEVICE FOR PARALLEL PROCESSING OF RETINAL IMAGES

A method for parallel processing of retinal images includes: optimizing an objective function with a chaotic supply-demand algorithm to enhance a real retinal image; synthesizing a virtual retinal image by a hybrid image generation method; establishing a parallel multi-layer decomposed interval type-2 intuitionistic fuzzy convolutional neural network model based on the virtual retinal image and the enhanced real retinal image; and integrating outputs from a plurality of parallel multi-layer decomposed interval type-2 intuitionistic fuzzy convolutional neural network models as a final classification result. 1. A method , comprising:1) optimizing an objective function with a chaotic supply-demand algorithm to enhance a real retinal image;2) synthesizing a virtual retinal image by a hybrid image generation method;3) establishing a parallel multi-layer decomposed interval type-2 intuitionistic fuzzy convolutional neural network model based on the virtual retinal image and the real retinal image enhanced; and4) integrating outputs from a plurality of parallel multi-layer decomposed interval type-2 intuitionistic fuzzy convolutional neural network models as a final classification result.2. The method of claim 1 , wherein 1) is implemented as follows: {'br': None, 'i': EI', 'i,j', 'M', 'I', 'i,j, '()=(()|θ)\u2003\u2003(1)'}, '1.1) performing function transformation M on an input original real retinal image to obtain an enhanced output image{'o': [{'@ostyle': 'single', 'P'}, {'@ostyle': 'single', 'P'}, {'@ostyle': 'single', 'P'}, {'@ostyle': 'single', 'P'}], 'sup': σ', 'n', 'n', '2', 'n', 'n', '2', '1/2, 'sub': p=1', 'q=1', 'p=1', 'q=1, 'where I(i, j) denotes a part of the input original real retinal image, and EI(i, j) denotes a corresponding part of an enhanced retinal image, i, j=1, 2, . . . , n; θ=(r, β, ρ, σ) is an undetermined parameter of the function (1); M(I(i, j)|θ)=M(I(i, j)|r, β, ρ, σ)=rP/(s(i, j)+β)(I(i, j)−p×(i, j))+(i, j) denotes an image enhancement function ...

IMAGE PROCESSING METHOD, PROGRAM, OPHTHALMIC DEVICE, AND CHOROIDAL BLOOD VESSEL IMAGE GENERATION METHOD

An image processing method comprising acquiring a first fundus image obtained by photographing a fundus using first light having a first wavelength, and a second fundus image obtained by photographing the fundus using second light having a second wavelength that is shorter than the first wavelength; specifying, in the first fundus image, respective positions of retinal blood vessels appearing in the second fundus image; and generating a choroidal blood vessel image by processing the positions identified in the first fundus image. 111-. (canceled)12. An image processing method comprising:acquiring a first fundus image obtained by photographing a fundus using first light having a first wavelength, and a second fundus image obtained by photographing the fundus using second light having a second wavelength that is shorter than the first wavelength;specifying, in the first fundus image, respective positions of retinal blood vessels appearing in the second fundus image; andgenerating a choroidal blood vessel image by processing the positions identified in the first fundus image.13. The image processing method according to claim 12 , wherein claim 12 , in generating the choroidal blood vessel image claim 12 , inpainting processing is performed on the positions specified in the first fundus image.14. The image processing method according to claim 12 , further comprising extracting the retinal blood vessels from the second fundus image claim 12 , wherein claim 12 ,in generating the choroidal blood vessel image, the retinal blood vessels extracted from the second fundus image are made inconspicuous in the first fundus image.15. The image processing method according to claim 12 , further comprising extracting the retinal blood vessels from the second fundus image claim 12 , wherein claim 12 ,in generating the choroidal blood vessel image, the retinal blood vessels extracted from the second fundus image are removed from the first fundus image.16. The image processing method ...

METHOD OF PROCESSING OPTICAL COHERENCE TOMOGRAPHY (OCT) DATA, METHOD OF OCT IMAGING, AND OCT DATA PROCESSING APPARATUS

An OCT apparatus of an exemplary aspect includes an OCT scanner, image data generating unit, registration unit, and image data composing unit. The OCT scanner is configured to acquire three dimensional data sets by applying an OCT scan to mutually different three dimensional regions of a sample. The image data generating unit is configured to generate a plurality of pieces of image data from the three dimensional data sets. The registration unit is configured to perform a first registration between the plurality of pieces of image data by applying an image correlation calculation to each of overlap regions in the plurality of pieces of image data. The image data composing unit is configured to compose the plurality of pieces of image data based on a result of the first registration. 1: A method of processing data acquired by an optical coherence tomography (OCT) scan , the method comprising:preparing a plurality of three dimensional data sets acquired from a plurality of three dimensional regions of a sample different from each other;generating a plurality of pieces of image data from the plurality of three dimensional data sets;performing a first registration between the plurality of pieces of image data by applying an image correlation calculation to each of a plurality of overlap regions in the plurality of pieces of image data; andcomposing the plurality of pieces of image data based on a result of the first registration.2: The OCT data processing method of claim 1 , wherein for a first image data and a second image data that include mutual overlap regions claim 1 , the image correlation calculation calculates at least one of a translation amount and a rotation amount between the overlap region in the first image data and the overlap region in the second image data.3: The OCT data processing method of claim 2 , wherein the image correlation calculation includes a phase only correlation calculation.4: The OCT data processing method of claim 1 , further comprising ...

SHAKING IMAGE FOR REGISTRATION VERIFICATION

A method and system are described that allow a user to verify a registration proposal during an image-guided ophthalmic surgery. The system configured to perform the method has a processor and a non-transitory computer-readable medium accessible to the processor containing instructions executable by the processor to perform the method. 1. A system configured for verifying , by a user , a proposed registration during ophthalmic surgery , the system comprising:a processor; and ["acquiring, from a photosensor, an intra-operative image of a patient's eye under magnification by a microscope;", "retrieving, from a non-transitory computer-readable medium, a pre-operative reference image of the patient's eye, wherein the limbus of the pre-operative image of the patient's eye has a center;", "performing a registration process to provide a proposed registration of the pre-operative reference image of the patient's eye and the intra-operative image of the patient's eye;", 'overlaying the pre-operative reference image and the intra-operative image to provide a merged image having the proposed registration, wherein the merged image is viewable by the user;', 'adjusting the transparency of at least one of the pre-operative reference image and the intra-operative image, so that the pre-operative reference image and the intra-operative image are simultaneously viewable in the merged image by the user; and', "rotating the viewable pre-operative reference image relative to the viewable intra-operative image comprised in the viewable merged image, wherein the rotating is centered on the center of the limbus of the patient's eye in the pre-operative reference image;"], 'a non-transitory computer-readable medium accessible to the processor containing instructions executable by the processor forthereby allowing the user to verify a proposed registration during ophthalmic surgery.2. The system of claim 1 , wherein the transparency is selected from between about 1-10% claim 1 , 10-20% ...

APPARATUS AND METHOD FOR CONSTRUCTING A VIRTUAL 3D MODEL FROM A 2D ULTRASOUND VIDEO

A method for creating a three-dimensional image of an object from a two-dimensional ultrasound video is provided. The method includes acquiring a plurality of two-dimensional ultrasound images of the object and recording a plurality of videos based on the acquired two-dimensional ultrasound images. Each of the videos includes a plurality of frames. The method further includes separating each of the plurality of frames, cropping each of the plurality of frames to isolate structures intended to be reconstructed, selecting a frame near a center of the object and rotating the image to create a main horizontal landmark, and aligning each frame to the main horizontal landmark. The method also includes removing inter-frame jitter by aligning each of the plurality of frames relative to a previous frame of the plurality of frames, reducing the noise of each of the frames, and stacking each of the frames into a three-dimensional volume. 1. A method for creating a three-dimensional image of an object from a two-dimensional ultrasound video , the method comprising:acquiring a plurality of two-dimensional ultrasound images of the object;recording a plurality of videos based on the acquired two-dimensional ultrasound images, each of the plurality of videos comprising a plurality of frames;separating each of the plurality of frames;cropping each of the plurality of frames to isolate structures intended to be reconstructed;selecting a frame near a center of the object and rotating the image to create a main horizontal landmark;aligning each of the plurality of frames to the main horizontal landmark; andstacking each of the aligned plurality of frames into a three-dimensional volume.2. The method according to claim 1 , further comprising:removing inter-frame jitter by aligning each of the plurality of frames relative to a previous frame of the plurality of frames.3. The method according to claim 1 , further comprising:reducing a noise of each of the plurality of frames.4. The method ...

Generalizable medical image analysis using segmentation and classification neural networks

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a final classification output for an image of eye tissue. The image is provided as input to each of one or more segmentation neural networks to obtain one or more segmentation maps of the eye tissue in the image. A respective classification input is generated from each of the segmentation maps. For each of the segmentation maps, the classification input for the segmentation map is provided as input to each of one or more classification neural networks to obtain, for each segmentation map, a respective classification output from each classification neural network. A final classification output for the image is generated from the respective classification outputs for each of the segmentation maps.

Augmented and virtual reality display systems and methods for delivery of medication to eyes

Configurations are disclosed for a health system to be used in various healthcare applications, e.g., for patient diagnostics, monitoring, and/or therapy. The health system may comprise a light generation module to transmit light or an image to a user, one or more sensors to detect a physiological parameter of the user's body, including their eyes, and processing circuitry to analyze an input received in response to the presented images to determine one or more health conditions or defects.

PUPIL ELLIPSE-BASED, REAL-TIME IRIS LOCALIZATION

The disclosure relates to systems, methods and programs for developing real-time user-specific eye model based on iris localization using solely pupil-ellipse analysis. 2. The method of claim 1 , wherein the step of identifying the major axis R of the projected pupil ellipse comprises:a. detecting a pupil ellipse in each image;b. determining the detected ellipse's major axis length;c. unprojecting each pupil ellipse to a circle in three-dimensional (3D) space; andd. combining unprojected circles from each image, thereby forming a 3D pupil motion model.3. The method of claim 2 , further comprising measuring a radius of the pupil along each of the pair of rays r claim 2 , inscribing limbus visibility angle θ claim 2 , establishing ray-specific radii r claim 2 , r claim 2 , for each image.4. The method of claim 3 , wherein the pupil center is established as the mid-point of the detected major axis R of the pupil ellipse.5. The method of claim 4 , wherein the steps of detecting limbus points LP claim 4 , and LPfor each edge-rendered image and compiling the user-specific eye-model comprise:{'sub': PL', 'PLq', 'PL1', 'PL2, 'a. for each ray inscribing limbus visibility angle θ, recording distance Dfrom the pupil center to the second detected edge in each edge-detected image thereby identifying D, and D, for each edge-rendered image;'}{'sub': PL1', 'PL2', 'P1', 'P2', 'N1', 'N2, 'b. normalizing each of Dand D, by the respective rand r, thereby identifying normalized distances Dand Dfor each edge-rendered image;'}{'sub': PL1', 'PL2, 'c. using a predetermined normalized distance range to establish a plurality of bins to build a histogram of Dand Dfrom one or more captured images;'}{'sub': 'Pi', 'd. multiplying each bin content by its corresponding r;'}{'sub': 'N', 'e. selecting the normalizing radius rfrom the histogram mode bin,'}{'sub': j', 'Pi', 'N, 'f. calculating limbus points (l) detected from one or more of the captured images constrained by r×r; and'}{'sub': j', 'j, 'g ...

Digital Image Optimization For Ophthalmic Surgery

The present disclosure provides a digital image optimization system including a camera that includes at least one sensor that detects light reflected off an eye and sends a signal corresponding to the detected light to a processor. The system further includes an image processing system including the processor and that executes instructions to produce a digital image of the eye. The image processing system also executes instructions to apply a digital image optimization algorithm including a trained machine-learning model to the digital image of the eye to generate an optimized digital image of the eye. The system further includes a digital display that displays the optimized digital image of the eye. 1. A digital image optimization system comprising:a camera comprising at least one sensor operable to detect light reflected off an eye and send a signal corresponding to the detected light to a processor;an image processing system comprising the processor and operable to:execute instructions to produce a digital image of the eye; and 'a digital display operable to display the optimized digital image of the eye.', 'execute instructions to apply a digital image optimization algorithm comprising a trained machine-learning model to the digital image of the eye to generate an optimized digital image of the eye; and'}2. The digital image optimization system of wherein the digital image optimization algorithm at least partially reduces instrument glare claim 1 , optical aberration claim 1 , vitreous fog claim 1 , or any combination thereof claim 1 , in the digital image of the eye to generate the optimized digital image of the eye.3. The digital image optimization system of wherein the optimized digital image of the eye has contrast claim 1 , sharpness claim 1 , clarity claim 1 , dynamic range claim 1 , or any combination thereof that is the same or increased than that of the digital image of the eye.4. The digital image optimization system of wherein the optimized digital ...

METHODS OF OBTAINING 3D RETINAL BLOOD VESSEL GEOMETRY FROM OPTICAL COHERENT TOMOGRAPHY IMAGES AND METHODS OF ANALYZING SAME

Embodiments relate to extracting blood vessel geometry from one or more optical coherent tomography (OCT) images for use in analyzing biological structures for diagnostic and therapeutic applications for diseases that can be detected by vascular changes in the retina. An OCT image refers generally to one or more images of any dimension obtained using any one or combination of OCT techniques. Some embodiments include a method of identifying a region of interest of a retina from a plurality of retinal blood vessels in at least one optical coherence tomography (OCT) image of at least a portion of the retina. Some embodiments include a method of distinguishing between a plurality of retinal layers from vessel morphology information of retinal blood vessels in at least one optical coherence tomography (OCT) image of at least a portion of the retina. 1. A method of identifying a 3D region of interest of a retina from a plurality of retinal blood vessels in a 3D optical coherence tomography (OCT) image , comprising more than one OCT image , of at least a portion of the retina , the method comprising:using at least one computer programmed to perform: obtaining a geometrical representation of a vascular tree or vessel network of retinal blood vessels from the 3D OCT image;evaluating at least one first morphological feature of a plurality of retinal blood vessels detected in the geometrical representation of the 3D OCT image at each of a plurality of voxel locations in the geometrical representation; andidentifying a first region of interest based at least in part on evaluating the at least one first morphological feature of the plurality of blood vessels, wherein the first region of interest comprises a particular retinal layer.2. The method of claim 1 , wherein identifying the first region of interest comprises constructing a likelihood function of voxels belong to the first region of interest and a smoothness constraint to force the first region of interest to be ...

IMAGE PROCESSING DEVICE, METHOD OF IMAGE PROCESSING, AND SURGICAL MICROSCOPE

The present technology relates to an image processing device, a method of image processing, and a surgical microscope that can detect and report a dangerous condition on the basis of a tomographic image during eye surgery. An image processing device includes: a dangerous condition detection unit configured to detect a dangerous condition on the basis of a tomographic image of an eye acquired during surgery of the eye; and a control information generation unit configured to generate and output control information used to manage the detected dangerous condition. The present technology is applicable to, for example, a surgical system used for eye surgery or other surgical procedures. 1. An image processing device comprising:a dangerous condition detection unit configured to detect a dangerous condition on the basis of a tomographic image of an eye acquired during surgery of the eye; anda control information generation unit configured to generate and output control information used to manage the detected dangerous condition.2. The image processing device according to claim 1 ,wherein the dangerous condition detection unit calculates a risk parameter on the basis of the tomographic image of the eye and detects the dangerous condition on the basis of the risk parameter.3. The image processing device according to claim 2 ,wherein the dangerous condition detection unit calculates a distance from a corneal vertex to an iridocorneal angle as the risk parameter and detects the dangerous condition.4. The image processing device according to claim 1 ,wherein the dangerous condition detection unit detects a shallow anterior chamber as the dangerous condition.5. The image processing device according to claim 2 ,wherein the dangerous condition detection unit calculates a distance from a corneal vertex to a lower end of a posterior capsule as the risk parameter and detects the dangerous condition.6. The image processing device according to claim 1 ,wherein the dangerous condition ...

SYSTEM AND METHOD FOR OBTAINING MEASUREMENTS FROM IMAGING DATA

Probabilistic measurements of objects in image data are obtained by analyzing individual segments of an image to determine the probability that an object is present in the segment, and aggregating the total probabilities among all of the segments in the image to provide an overall probabilistic measurement of the object. For example, pixels of an OCT image can be assigned probabilities that the pixel contains a retinal layer or background. The sum of probabilities of the retinal layer being present in a one-dimensional row of pixels gives a probabilistic length in that dimension of the retinal layer. Likewise, the sum of a two-dimensional array of pixels gives an area; and a three-dimensional array gives a volume. 1. A method for measuring an object in an image , the method comprising:segmenting an image into a plurality of segments;obtaining a probabilistic value for each of the plurality of segments, the probabilistic value corresponding to a likelihood of an object being in each of the plurality of segments; andaggregating the probabilistic values from the plurality of segments to obtain a measurement for the object.2. The method of claim 1 , wherein the image comprises multiple classes of objects.3. The method of claim 2 , further comprising obtaining probabilistic values for each of the multiple classes of objects.4. The method of claim 2 , wherein the multiple classes of objects comprise one or more of: a retinal layer claim 2 , a fluid pocket claim 2 , lesion claim 2 , cyst claim 2 , and background.5. The method of claim 1 , wherein the image is an OCT image.6. The method of claim 1 , wherein the plurality of segments comprise pixels.7. The method of claim 1 , wherein the measurements are distances claim 1 , areas claim 1 , volumes claim 1 , distances over time claim 1 , areas over time claim 1 , or volumes over time.8. The method of claim 1 , wherein the probabilistic values are between 0 and 1 claim 1 , inclusive.9. The method of claim 1 , wherein the ...

METHODS AND SYSTEMS FOR LASER SCAN LOCATION VERIFICATION AND LASER SURGICAL SYSTEMS WITH LASER SCAN LOCATION VERIFICATION

A method of verifying a laser scan at a predetermined location within an object includes imaging at least a portion of the object, the resulting image comprising the predetermined location; identifying the predetermined location in the image, thereby establishing an expected scan location of the laser scan in the image; performing a laser scan on the object by scanning a focal point of the laser beam in a scanned area; detecting a luminescence from the scanned area and identifying an actual scanned location within the image based on the detected luminescence; and determining whether the difference between the actual scanned location and the expected scan location is within a threshold value. 1. A method of verifying the placement a laser scan at a predetermined location within an object , comprising:imaging at least a portion of the object, the resulting image comprising the predetermined location;identifying the predetermined location in the image, thereby establishing an expected scan location of the laser scan in the image;performing the laser scan on the object by scanning a focal point of a laser beam in a scanned area;detecting a luminescence from the scanned area and identifying an actual scanned location within the image based on the detected luminescence; andverifying whether the laser scan was at the predetermined location based on a difference between the actual scanned location and expected scan location.2. The method of claim 1 , wherein the object is a human eye.3. The method of claim 1 , wherein the object is a calibration apparatus.4. The method of claim 1 , wherein the laser beam is a pulsed laser beam having a wavelength of 320 nm to 370 nm.5. The method of claim 1 , wherein the luminescence has a wavelength of 400 nm or more.6. The method of claim 1 , wherein the image comprises an array of pixels.7. The method of claim 6 , wherein the expected location comprises one or more pixels selected from amongst the array of pixels.8. The method of claim 6 ...

VEHICLE SAFETY SYSTEM AND OPERATING METHOD THEREOF

There is provided a vehicle safety system including a sensing unit, a processing unit, a control unit and a display unit. The sensing unit is configured to capture an image frame containing an eyeball image from a predetermined distance. The processing unit is configured to calculate a pupil position of the eyeball image in the image frame and generate a drive signal corresponding to the pupil position. The control unit is configured to trigger a vehicle device associated with the pupil position according to the drive signal. The display unit is configured to show information of the vehicle device. 1. A vehicle safety system comprising:a sensing unit configured to capture an image frame containing an eyeball image of an eyeball from a predetermined distance;a processing unit configured to calculate a pupil position of the eyeball image in the image frame and generate a drive signal corresponding to the pupil position; anda control unit configured to trigger a vehicle device associated with the pupil position according to the drive signal.2. The vehicle safety system as claimed in claim 1 , further comprising:a light source configured to emit light toward the eyeball to generate at least one glint on the eyeball,wherein the processing unit is configured to determine the pupil position according to a spatial relationship between a pupil image and at least one glint image in the image frame.3. The vehicle safety system as claimed in claim 1 , wherein the eyeball image is divided into at least two sub-regions to respectively correspond to different functions; and the processing unit is configured to respectively calculate a gray value of each of the at least two sub-regions and identify the pupil position as one of the two sub-regions according to the calculated gray values.4. The vehicle safety system as claimed in claim 3 , wherein the gray value is an average gray value or a summation of gray values.5. The vehicle safety system as claimed in claim 1 , wherein the ...

IMAGE PROCESSING APPARATUS AND IMAGE PROCESSING METHOD

An image processing apparatus includes an alignment unit configured to align a first fundus oculi image that is an aberration-corrected image of an eye being examined and a second fundus oculi image having a larger view angle and a lower resolution than the first fundus oculi image, by using a third fundus oculi image having a smaller view angle and a higher resolution than the second fundus oculi image; a distance acquisition unit configured to acquire a distance from a macula lutea of the eye being examined to a certain position in the first fundus oculi image aligned by the alignment unit; and an evaluation unit configured to evaluate the state of the eye being examined from the distance and information concerning photoreceptor cells included in the first fundus oculi image. 1. An image processing apparatus comprising:an acquisition unit configured to acquire a first fundus oculi image, a second fundus oculi image and a third fundus oculi image, the first fundus oculi image being an aberration-corrected image of an eye being examined, the second fundus oculi image being an image having a larger view angle and a lower resolution than the first fundus oculi image, the third fundus oculi image being an image having a smaller view angle and a higher resolution than the second fundus oculi image;an alignment unit configured to align a first fundus oculi image and a second fundus oculi image by using a third fundus oculi image.2. The image processing apparatus according to claim 1 , wherein the alignment unit aligns the first fundus oculi image and the second fundus oculi image in accordance with a result of alignment between the second fundus oculi image and the third fundus oculi image and a result of alignment between the third fundus oculi image and the first fundus oculi image.3. The image processing apparatus according to claim 1 , further comprising:a display control unit configured to cause a display unit to display the first fundus oculi image and the second ...

Image processing apparatus, image processing method, and program therefor

Provided is an image processing apparatus configured to process an image of a fundus of an eye, which is capable of simply and accurately measuring a distribution of cells that form a blood vessel wall of an eye. The image processing apparatus includes: an image acquiring unit configured to acquire an image of an eye; a vessel feature acquiring unit configured to acquire membrane candidate points that form an arbitrary wall of a blood vessel based on the acquired image; and a cell identifying unit configured to identify a cell that forms the wall of the blood vessel based on the membrane candidate points.

APPLICATION TO DETERMINE READING/WORKING DISTANCE

A method of measuring working distance between a handheld digital device and eyes of a user, including capturing an image of at least eyes of a user via an onboard camera of the handheld digital device while the user is viewing a display of the handheld digital device and comparing an apparent angular size of a structure of the eyes or face of the user to a previously captured image of the structure of the eyes or the face that was taken in the presence of an object of known size. The method further includes calculating a working distance based on the apparent angular size of the structure of the eyes or the face; and saving at least the working distance to memory or reporting out the calculated working distance on the display. A handheld digital device programmed with an algorithm to perform the method is also included. 1. A computer implemented method of assessing reading ability of a user , comprising:presenting a reading stimulus to patient on a display of a handheld digital device;determining a working distance between the handheld digital device and eyes of the user; andsaving at least the working distance determined to memory, reporting out the determined working distance on the display or both.2. The computer implemented method as claimed in claim 1 , further comprising calibrating a processor of the handheld digital device by capturing an image of eye structures claim 1 , facial structures or both while including an object of known size in the captured image.3. The computer implemented method as claimed in claim 2 , further comprising determining a size of the eye structures claim 2 , facial structures or both relative to the object of known size in the captured image.4. The computer implemented method as claimed in claim 1 , further comprising determining the working distance directly or on the basis of comparison to the object of known size.5. The computer implemented method as claimed in claim 1 , further comprising making a record of font size of ...

METHODS FOR DETECTION AND ENHANCED VISUALIZATION OF PATHOLOGIES IN A HUMAN EYE

Various methods for the detection and enhanced visualization of a particular structure or pathology of interest in a human eye are discussed in the present disclosure. An example method to visualize a given pathology (e.g., CNV) in an eye includes collecting optical coherence tomography (OCT) image data of the eye from an OCT system. The OCT image data is segmented to identify two or more retinal layer boundaries located in the eye. The two or more retinal layer boundaries are located at different depth locations in the eye. One of the identified layer boundaries is moved and reshaped to optimize visualization of the pathology located between the identified layer boundaries. The optimized visualization is displayed or stored or for a further analysis thereof. 1. A method for visualizing a pathology in an eye , said method comprising:collecting three-dimensional optical coherence tomography (3D-OCT) image data of the eye from an OCT system;obtaining an initial slab from the 3D-OCT image data, the initial slab having a predefined upper limit and a predefined lower limit and containing the pathology within the upper and lower limits;generating a reference map based on the pathology to be visualized, said reference map being generated from the 3D-OCT image data and containing maximum values in the en face locations where the pathology is located and minimum values in other background en face regions;optimizing the upper and/or lower limits of the initial slab using the reference map for the visualization of the pathology;generating a final slab based on the optimized upper and lower limits, wherein the en face projection of the final slab depicts the pathology with improved clarity; anddisplaying or storing the final slab or a further analysis thereof.2. The method as recited in further comprising:calculating motion contrast information in the 3D-OCT image data using an OCT angiography (OCTA) processing technique to obtain OCTA image data, wherein the initial slab is ...

A SYSTEM AND METHOD OF ARTIFICIAL INTELLIGENCE AND TOMOGRAPHY IMAGING OF HUMAN CORNEA

The invention relates to a system and method of implementation of artificial intelligence and tomography imaging to determine the biomechanical degradation or degeneration in human cornea. The invention relates to a combination tool using artificial intelligence and tomography imaging to map the region of degeneration in the cornea. The method of artificial intelligence and corneal tomography imaging includes analysis of changes in the structure of the cornea, constructing the 3D volumes using corneal tomography, meshing the 3D volumes with the elements for biomechanical simulations by using finite element modules, application of artificial intelligence to determine the region of biomechanical degeneration in cornea. The combination tool of the invention is effective in predicting the progression of the disease by analyzing the chronic steepening of the cornea by quantitating the parameters such as increase in curvature, aberrations of the cornea. 1. A system to determine one or more regions of biomechanical degradation of human cornea , the system comprises:a. a corneal tomography to map the surface curvature of cornea;b. a finite element simulation module to compute one or more deformations in cornea; andc. an artificial intelligence module to determine one or more regions of biomechanical degeneration in cornea.2. The system as claimed in claim 1 , wherein the corneal tomography analyses the anterior and posterior corneal surfaces with elevation and curvature to reconstruct 3D (Dimensional) or 2D structure of the cornea.3. The system as claimed in claim 1 , wherein the finite element simulation module utilizes ray tracing for one or more computing aberrations after populating with biomechanical properties of the cornea.4. The system as claimed in claim 1 , wherein the artificial intelligence module determines biomechanical degeneration by using longitudinal tomography maps of the same eye or a single cross-section tomography of the eye referenced to a normative ...

IMAGE DISPLAY APPARATUS, METHOD OF PROCESSING, AND PROCESSING APPARATUS

An image display apparatus includes: a light source part generating a plurality of light rays corresponding to respective pixels in an image that changes over time; a projecting part defining an optical path from the light source part to an eye, and forming the image on a retina of the eye by projecting the generated light rays directly on the retina through the optical path; a splitting part splitting a plurality of reflection light rays from positions in a certain site of the eye on the optical path, the positions corresponding to the respective pixels; a detecting part detecting intensities of the reflection light rays that have been split; and a processing part obtaining parameters indicative of conditions of the site at the positions corresponding to the respective pixels, based on intensities of the generated light rays and the intensities of the reflection light rays, for the respective pixels. 1. An image display apparatus comprising:a light source part that generates a plurality of light rays corresponding to respective pixels in an image that changes over time;a projecting part that defines an optical path from the light source part to an eye, and forms the image on a retina of the eye by projecting the plurality of generated light rays directly on the retina through the optical path;a splitting part that splits a plurality of reflection light rays from positions in a certain site of the eye on the optical path, the positions corresponding to the respective pixels;a detecting part that detects intensities of the plurality of reflection light rays that have been split; anda processing part that obtains parameters indicative of conditions of the site at the positions corresponding to the respective pixels, based on intensities of the generated light rays and the intensities of the plurality of reflection light rays, for the respective pixels.2. The image display apparatus according to claim 1 , whereinthe obtainment of the parameter comprises dividing an ...

SYSTEMS AND METHODS FOR IMPROVED ANTERIOR SEGMENT OCT IMAGING

Various methods and systems for improved anterior segment optical coherence tomography (OCT) imaging are described. One example method includes collecting a set of OCT data of the cornea of the eye; segmenting the set of OCT data to identify one or more corneal layers; fitting a two-dimensional model of corneal surfaces to the one or more corneal layers; determining motion-correction parameters by minimizing error between the one or more corneal layers and the two-dimensional model of the corneal surfaces; and creating a motion-corrected corneal image dataset from the set of OCT data using the motion-correction parameters. The motion-corrected corneal image dataset can be used to create a model of the anterior and/or posterior surfaces of the cornea. The model of the cornea is used to generate high density and motion-artifact free epithelial thickness maps, which are used for identifying or quantifying pathology such as keratoconus. 1. A method of motion correction in corneal image data of an eye using an optical coherence tomography (OCT) system , said method comprising:collecting a set of OCT data of the cornea of the eye using the OCT system;segmenting the set of OCT data to identify one or more corneal layers;fitting a two-dimensional model of corneal surfaces to the one or more corneal layers;determining motion-correction parameters by minimizing error between the one or more corneal layers and the two-dimensional model of the corneal surfaces;creating a motion-corrected corneal image dataset from the set of OCT data using the motion-correction parameters; andstoring or displaying the motion-corrected corneal image dataset or information derived from the motion-corrected corneal image dataset.2. The method as recited in claim 1 , wherein the set of OCT data consists of B-scans over a series of transverse locations on the cornea of the eye.3. The method as described in claim 1 , wherein the set of OCT data includes one or both of axial and transverse eye motion ...

ACQUISITION AND ANALYSIS TECHNIQUES FOR IMPROVED OUTCOMES IN OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY

Methods for improved acquisition and processing of optical coherence tomography (OCT) angiography data are presented. One embodiment involves improving the acquisition of the data by evaluating the quality of different portions of the data to identify sections having non-uniform acquisition parameters or non-uniformities due to opacities in the eye such as floaters. The identified sections can then be brought to the attention of the user or automatically reacquired. In another embodiment, segmentation of layers in the retina includes both structural and flow information derived from motion contrast processing. In a further embodiment, the health of the eye is evaluating by comparing a metric reflecting the density of vessels at a particular location in the eye determined by OCT angiography to a database of values calculated on normal eyes. 118-. (canceled)19. A method for acquiring wide-field optical coherence tomography (OCT) angiography image data of an eye using an OCT system having an adjustable refractive correction , comprising:acquiring a first OCT angiography dataset with the OCT system at a first refractive correction over a first region of the eye;analyzing the curvature of the eye in the first dataset near an edge of the first region;acquiring a second OCT dataset with the OCT system at a second refractive correction value over a second region of the eye, said second region at least partially overlapping the edge of the first region and wherein, said second refractive correction value is based on the results of the analysis of the curvature of the eye,generating a single image of the eye from the first and second datasets; andstoring or displaying the generated image or a further analysis thereof.20. The method as recited in claim 19 , further comprising repeating the acquiring and analyzing steps for a plurality of partially overlapping regions wherein the curvature near an edge of the most recently acquired OCT data set is analyzed and the analyzed ...

IMAGING SYSTEM AND METHOD FOR DIAGNOSTIC IMAGING

An imaging system and method for using an optical device with an electronic device for diagnostic imaging is provided. The imaging system may include a controller configured to capture a series of holograms by powering a light source of the optical device to illuminate an object, wherein light from the light source is collimated onto the object through an aperture of the optical device. The controller may be configured to extract an interference pattern of the object from the series of holograms, wherein the interference pattern is produced by interference between a reflected beam from the object and a reference beam formed by a diffraction mirror of the optical device. The controller may be configured to record at least one image of the object based on the interference pattern. The imaging system may include a data storage configured to store the at least one image.

AUTOMATED BLOOD VESSEL FEATURE DETECTION AND QUANTIFICATION FOR RETINAL IMAGE GRADING AND DISEASE SCREENING

A method for vessel mapping and quantification. The method comprises pre-processing a retinal image to generate a vessel segmented image and processing the vessel segmented image to generate an image with a central light reflex. The method further includes identifying a cylindrical or tube-shaped region in the central light reflex and determining a closed contour representing the cylindrical shaped region and representing the closed contour by a function. The method computes a ratio of a minimum and maximum radius of the cylinder to determine an average shape of the cylinder associated with the central light reflex by using the function. The image is further processed to apply a morphological skeletonization operation to generate vessel centerlines and the segmented vascular network of the retinal image. In an example embodiment, a method for artery-vein nicking quantification for retinal blood vessels is performed by computing width of the vessel near and away from a cross over point of the vessels. In another example embodiment, a feature associate with the central light reflex is identified and compared with a second feature in the same location evaluated at a different time zone to confirm the associated shape of the light reflex. In another example embodiment, retinal focal arteriolar narrowing (FAN) is identified and quantified value is generated. In another example embodiment, a true optic disc is identified based on a combination of features and parameters associate with the vessel. 1. A method for vessel classification , the method comprising:pre-processing a retinal image to generate a vessel segmented image;first processing the vessel segmented image to generate an image with a central light reflex;identifying a cylindrical shaped region in the central light reflex;determining a closed contour representing the cylindrical shaped region and representing the closed contour by a function;computing a ratio of a minimum and maximum radius of the cylindrical ...

Skin condition detection method and electronic device

A skin condition detection method and an electronic device are provided. The method includes: acquiring a first image; performing at least one skin condition detection on the first image to acquire at least one first characteristic value; acquiring at least one second characteristic value acquired through the skin condition detection in the second image; determining whether a skin condition in the first image has changed with respect to a skin condition in the second image according to the first characteristic value and the second characteristic value; and if the skin condition in the first image has changed with respect to the skin condition in the second image, outputting notification information to indicate that the skin condition in the first image has changed with respect to the skin condition in the second image. The invention makes it possible to effectively and clearly determine change of the skin condition.

SYSTEMS AND METHODS FOR INTRAOCULAR LENS SELECTION

Systems and methods for intraocular lens selection include receiving, by one or more computing devices implementing a prediction engine, pre-operative multi-dimensional images of an eye; extracting, by the prediction engine, pre-operative measurements of the eye based on the pre-operative images; estimating, by the prediction engine using a prediction model based on a machine learning strategy, a post-operative position of an intraocular lens based on the extracted pre-operative measurements; selecting a power of the intraocular lens based on the estimated post-operative position of the intraocular lens; and selecting the intraocular lens based on the selected power. In some embodiments, the systems and methods further include receiving post-operative multi-dimensional images of the eye after implantation of the selected intraocular lens, extracting post-operative measurements of the eye, and updating the prediction model based on the pre-operative measurements and the post-operative measurements. 1. A method comprising:receiving, by one or more computing devices implementing a prediction engine, one or more pre-operative multi-dimensional images of an eye;extracting, by the prediction engine, one or more pre-operative measurements of the eye based on the one or more pre-operative images of the eye;estimating, by the prediction engine using a first prediction model based on a machine learning strategy, a post-operative position of an intraocular lens based on the one or more extracted pre-operative measurements of the eye;selecting a power of the intraocular lens based on at least the estimated post-operative position of the intraocular lens; andselecting the intraocular lens based on at least the selected power.2. The method of claim 1 , further comprising:receiving one or more post-operative multi-dimensional images of the eye after implantation of the selected intraocular lens;extracting one or more post-operative measurements of the eye; andupdating the first ...

APPARATUS, METHOD, AND PROGRAM FOR PROCESSING IMAGE

A high-resolution image suited to the purpose of a doctor or the like is acquired. The present invention relates to an image processing apparatus including an acquisition unit configured to acquire a tomogram of a subject eye; a first extraction unit configured to extract part of the tomogram acquired by the acquisition unit; an estimating unit configured to estimate a high-frequency component based on a result of extraction by the extraction unit; and a combining unit configured to combine the high-frequency component with the tomogram acquired by the acquisition unit. 1. An image processing apparatus comprising:an acquisition unit configured to acquire a tomogram of a subject eye;a first extraction unit configured to extract part of the tomogram acquired by the acquisition unit;an estimating unit configured to estimate a high-frequency component based on a result of extraction by the extraction unit; anda combining unit configured to combine the high-frequency component with the tomogram acquired by the acquisition unit.2. The image processing apparatus according to claim 1 , wherein the first extraction unit extracts a region for use in diagnosis as part of the tomogram acquired by the acquisition unit.3. The image processing apparatus according to claim 1 , wherein the first extraction unit extracts at least one of a layer boundary and a granular object as part of the tomogram acquired by the acquisition unit.4. The image processing apparatus according to claim 1 , further comprising:a difference acquisition unit configured to acquire a difference between a reference image obtained by scaling up and down the tomogram acquired by the acquisition unit and the tomogram acquired by the acquisition unit,wherein the estimating unit estimates a high-frequency component based on the difference obtained by the difference acquisition unit and the result of extraction.5. The image processing apparatus according to claim 3 , further comprising:an image acquisition unit ...

EYE CARE DEVICE AND METHOD FOR ASSESSING AND PREDICTING DEMENTIA

An establishing method of a retinal layer thickness detection model includes following steps. A reference database is obtained, and an image pre-processing step, a feature selecting step, a training step and a confirming step are performed. The reference database includes reference optical coherence tomographic images. In the image pre-processing step, the reference optical coherence tomographic images are duplicated and cell segmentation lines of retinal layers are marked to obtain control optical coherence tomographic images. In the feature selecting step, the reference optical coherence tomographic images are analyzed to obtain reference image features. The training step is to train with the reference image features and obtain the retinal layer thickness detection model. In the confirming step, marked optical coherence tomographic images are output by the retinal layer thickness detection model, and compared with the control optical coherence tomographic images to confirm an accuracy of the retinal layer thickness detection model. 1. A method for assessing and predicting dementia , comprising:obtaining a reference database, wherein the reference database comprises a plurality of reference optical coherence tomographic images;performing an image pre-processing step to duplicate each of the plurality of reference optical coherence tomographic images and mark a cell segmentation line of each of retinal layers, so as to obtain a plurality of control optical coherence tomographic images;performing a feature selecting step to analyze each of the plurality of reference optical coherence tomographic images by a feature selecting module, and obtain at least one reference image feature from each of the plurality of reference optical coherence tomographic images, so as to obtain a plurality of the reference image features;performing a training step to train with the plurality of the reference image features through a convolution neural network learning classifier to reach ...

Controller, position determination device, position determination system, display system, program, and recording medium

A controller is configured to determine a position of an object point in a real space, based on a cornea image of a first eye and a cornea image of a second eye of a user who is viewing the object point, in a captured image generated by imaging the first and second eyes of the user by an imaging device.

IMAGE PROCESSING APPARATUS OPHTHALMOLOGIC IMAGING SYSTEM AND IMAGE PROCESSING METHOD

An image processing apparatus includes an identifying unit configured to identify a region relating to the movement of blood cells on a fundus image captured by an ophthalmologic imaging apparatus that includes an adaptive optics system, and an acquisition unit configured to acquire information relating to a tissue that is positioned on a back side of a position where the movement of blood cells is recognized, when it is seen from an anterior eye part side, in the identified region.

Edge detection in images

An edge detection engine operates to scan an image to identify edges within the image. An annular aperture is used to locate the edges in the image. An output image is generated by the edge detection engine that identifies the locations of the edges found in the image.

ADAPTIVE ADJUSTMENT OF OVERLAY IMAGE PARAMETERS

Image parameters of an overlay image may be adjusted based on image parameters of an optical image displayed in a surgical microscope. The overlay image may then be displayed with the optical image to a user of the surgical microscope. 1. A method for image processing , the method comprising:receiving an overlay image for display with an optical image generated by a surgical microscope;scanning the optical image to generate optical image parameters;based on the optical image parameters, generating overlay image parameters to correspond to the optical image parameters;applying the overlay image parameters to the overlay image; anddisplaying the overlay image having the overlay image parameters with the optical image.2. The method of claim 1 , wherein displaying the overlay image further comprises:overlaying the overlay image onto a portion of the optical image.3. The method of claim 1 , wherein the overlay image includes transparent portions claim 1 , and wherein displaying the overlay image further comprises:overlaying the overlay image onto the optical image, wherein the overlay image and the optical image are the same size.4. The method of claim 1 , wherein the optical image parameters and the overlay image parameters include at least one of:brightness;contrast; andcolor scale.5. The method of claim 1 , wherein the overlay image includes optical scan data from an optical scanner.6. The method of claim 1 , wherein displaying the overlay image further comprises:outputting the overlay image to an ocular of the surgical microscope.7. The method of claim 1 , wherein generating the overlay image parameters to correspond to the optical image parameters further comprises:matching the overlay image parameters to the optical image parameters.8. An image processing system comprising: receive an overlay image for display with an optical image generated by a surgical microscope;', 'scan the optical image to generate optical image parameters;', 'based on the optical image ...

Information processing apparatus, information processing method, and program

An information processing apparatus according to an embodiment of the present technology includes an acquisition section and a processor. The acquisition section acquires eye information regarding an eye of a user. The processor determines a first line-of-sight direction on the basis of the eye information using a first method, determines a second line-of-sight direction on the basis of the eye information using a second method that is different from the first method, calculates reliability information regarding at least one of reliability of the first line-of-sight direction or reliability of the second line-of-sight direction, and determines a line-of-sight direction of the user on the calculated reliability information.

Image processing method, program, and image processing device

A visualization of choroidal blood vessel size is created. A vortex vein position is detected from a choroidal vascular image in which choroidal blood vessels have been visualized. Image processing is employed on the choroidal vascular image to extract first size choroidal blood vessels of a first size and to extract second size choroidal blood vessels of a second size different to the first size from the choroidal vascular image. A size analysis fundus image is generated in which a rectangular frame indicating the vortex vein position is displayed superimposed on the choroidal vascular image, and in which the first size choroidal blood vessels are displayed in red and the second size choroidal blood vessels are displayed in blue.

FUNCTIONAL OCT DATA PROCESSING

A method of processing functional OCT image data, acquired by an OCT scanner scanning a retina that is being repeatedly stimulated by a light stimulus, to obtain a response of the retina to the light stimulus, comprising: receiving OCT image data generated by the OCT scanner repeatedly scanning the retina over a time period, and a sequence of stimulus indicators each indicative of a stimulation of the retina by the light stimulus in a respective time interval of a sequence of time intervals spanning the time period; calculating, for each stimulus indicator, a product of the stimulus indicator and a respective windowed portion of the sequence of B-scans comprising a B-scan based on a portion of the OCT image data generated while the retina was being stimulated in accordance with the stimulus indicator; and combining the calculated products to generate the indication of the response. 1. A non-transitory computer-readable storage medium storing computer program instructions which , when executed by a computer processor , cause the computer processor to perform a method of processing functional OCT image data , which has been acquired by an OCT imaging device scanning a retina of a subject while the retina is being repeatedly stimulated by a light stimulus , to generate an indication of a response of the retina to the light stimulus , the method comprising: OCT image data that has been generated by the OCT imaging device repeatedly scanning a scanned region of the retina over a time period, and', 'stimulus data defining a sequence of stimulus indicators each being indicative of a stimulation of the retina by the light stimulus in a respective time interval of a sequence of time intervals that spans the time period; and, 'receiving, as the functional OCT image data calculating, for each stimulus indicator, a product of the stimulus indicator and a respective windowed portion of the sequence of B-scans comprising a B-scan which is based on a portion of the OCT image data ...

IMAGE PROCESSING METHOD, PROGRAM, IMAGE PROCESSING DEVICE, AND OPHTHALMIC SYSTEM

In the present invention, vortex vein positions are detected from a fundus image. The image processing method comprising: a step in which a choroidal blood vessel structure is analyzed from a fundus image; and a step in which vortex vein positions are detected based on the choroidal blood vessel structure. 119.-. (canceled)20. An image processing method comprising:analyzing a fundus image to find a direction of a choroidal blood vessel; anddetecting a position of a vortex vein based on the direction of the choroidal blood vessel.21. The image processing method according to claim 20 , characterized in that a vortex vein position-displayed fundus image in which the vortex vein positions are displayed on the fundus image is generated.22. The image processing method according to claim 20 , wherein the analyzing includes analyzing the choroidal blood vessel running direction.23. The image processing method according to claim 20 , wherein the analyzing includes analyzing whether or not a orientation of the choroidal blood vessels in the fundus image are in a radial configuration.24. The image processing method according to claim 22 , wherein the detecting of the vortex vein position includes detecting a vortex vein candidate based on a choroidal vascular structure and identifying whether or not the vortex vein candidate is a vortex vein.25. The image processing method according to claim 24 , wherein the identification of whether or not the vortex vein candidate is the vortex vein includes analyzing whether or not the choroidal blood vessels in the fundus image converge at the vortex vein candidate position.26. The image processing method according to claim 24 , wherein the identification of whether or not the vortex vein candidate is the vortex vein includes calculating characteristic quantities in a choroidal image of a periphery of the vortex vein candidates.27. The image processing method according to claim 26 , wherein the identification of whether or not the vortex ...

IRIS RECOGNITION VIA PLENOPTIC IMAGING

Iris recognition can be accomplished for a wide variety of eye images by using plenoptic imaging. Using plenoptic technology, it is possible to correct focus after image acquisition. One example technology reconstructs images having different focus depths and stitches them together, resulting in a fully focused image, even in an off-angle gaze scenario. Another example technology determines three-dimensional data for an eye and incorporates it into an eye model used for iris recognition processing. Another example technology detects contact lenses. Application of the technologies can result in improved iris recognition under a wide variety of scenarios. 18-. (canceled)9. A method implemented at least in part by a computing system , the method comprising:receiving a plenoptic iris image depicting an iris;from the plenoptic iris image depicting an iris, determining a three-dimensional shape of the iris;storing the three-dimensional shape of the iris; andapplying the three-dimensional shape of the iris as part of iris recognition processing.10. The method of wherein:determining a three-dimensional shape of the iris comprises:computing a depth map of the plenoptic iris image;segmenting the iris as depicted in the plenoptic iris image; andregistering the segmented iris to the depth map.11. The method of wherein:applying the three-dimensional shape of the iris as part of iris recognition processing comprises:constructing a personalized eye model based on the three-dimensional shape of the iris; andperforming iris recognition via the personalized eye model.12. The method of wherein:applying the three-dimensional shape of the iris as part of iris recognition processing comprises:constructing a personalized eye model based on the three-dimensional shape of the iris;via the personalized eye model, reconstructing a frontal view of an iris depicted in an off-angle iris image; andperforming iris recognition with the reconstructed frontal view.13. The method of further comprising ...

IRIS RECOGNITION VIA PLENOPTIC IMAGING

Iris recognition can be accomplished for a wide variety of eye images by using plenoptic imaging. Using plenoptic technology, it is possible to correct focus after image acquisition. One example technology reconstructs images having different focus depths and stitches them together, resulting in a fully focused image, even in an off-angle gaze scenario. Another example technology determines three-dimensional data for an eye and incorporates it into an eye model used for iris recognition processing. Another example technology detects contact lenses. Application of the technologies can result in improved iris recognition under a wide variety of scenarios. 117-. (canceled)18. A method implemented at least in part by a computing system , the method comprising:receiving a plenoptic iris image depicting an iris;from the plenoptic iris image depicting an iris, determining a three-dimensional shape of the iris;storing the three-dimensional shape of the iris;applying the three-dimensional shape of the iris as part of iris recognition processing; andbased on the three-dimensional shape of the iris, determining that no obfuscating contact lens is present.19. A method implemented at least in part by a computing system , the method comprising:receiving a plenoptic iris image depicting an apparent iris;from the plenoptic iris image depicting an apparent iris, computing a geometric shape of the apparent iris;storing the geometric shape of the apparent iris;comparing the geometric shape of the apparent iris against one or more characteristics of a contact lens; andresponsive to determining that the geometric shape of the apparent iris matches the one or more characteristics of the contact lens, sending a message to an iris recognition system indicating that an apparent iris in the plenoptic iris image is covered by a contact lens.20. The method of wherein:the one or more characteristics of the contact lens comprise a threshold curvature; andcomparing the geometric shape of the ...

WEARABLE EYE-TRACKING SYSTEM

An eye-tracking system includes a light-transmitting display module, a reflecting mirror, an image system, and a processing unit. The light-transmitting display module includes a first side and a second side. The imaging system is disposed on the second side of the light-transmitting display module and includes a camera lens and an image sensor. The camera lens is coated with an optical film for receiving the light reflected by a user face. The image sensor is configured to provide an eye image based on the light reflected by the user face. The processing unit is configured to analyze the eye image so as to acquire the facial characteristics associated with the eyes of the user, wherein the user face is located on the first side of the light-transmitting display module when the user puts on the eye-tracking system. 1. An eye-tracking system , comprising:a light-transmitting display module comprising a first side and a second side; a camera lens coated with an optical film for receiving light reflected by a face of a user; and', 'an image sensor configured to provide an eye image based on the light reflected by the face of the user; and, 'an imaging system disposed on the second side of the light-transmitting display module and comprisinga processing unit configured to acquire ocular characteristic information of the user by analyzing the eye image, wherein the face of the user is located on the first side of the light-transmitting display module when the user puts on the eye-tracking system.2. The eye-tracking system according to claim 1 , wherein the light-transmitting display module comprises:a micro display panel for providing a near-eye real image; anda lens configured to form a virtual image by enlarging the near-eye image so as to provide a virtual panoramic space.3. The eye-tracking system according to claim 1 , wherein the light-transmitting display module comprises an optical combiner.4. The eye-tracking system according to claim 1 , wherein the ocular ...

Systems and methods of choroidal neovascularization detection using optical coherence tomography angiography

Disclosed are systems and methods to automatically detect choroidal neovascularization (CNV) in the outer retina using OCT angiography. Further disclosed are methods of removing projection artifacts from the outer retina and for combining brightness, orientation, and position information in a context-aware saliency model to quantify CNV area in OCT angiograms.

Ophthalmological diagnosis device

There is provided a technique for reducing a burden on a patient during an examination and presenting an objective examination result. An ophthalmological diagnosis device ( 102 ) for providing information to assist in making a diagnosis on a cornea includes: an input unit that receives an input of video image data from an external device ( 101 ); an output unit that outputs image data; a storage unit that stores an evaluation criterion for an injury of the cornea; and a processing unit that processes data. The processing unit generates a diagnosis image based on a position of the cornea in each still image of the video image data, the processing unit divides the cornea captured in the generated diagnosis image into a plurality of regions, and evaluates an injury in each of the divided regions based on the evaluation criterion, the processing unit generates diagnosis information ( 204 ) in which the diagnosis image and information about the evaluation on the injury in each of the regions are superimposed on each other, and the processing unit outputs the diagnosis information ( 204 ) through the output unit.

NEURAL NETWORK FOR EYE IMAGE SEGMENTATION AND IMAGE QUALITY ESTIMATION

Systems and methods for eye image segmentation and image quality estimation are disclosed. In one aspect, after receiving an eye image, a device such as an augmented reality device can process the eye image using a convolutional neural network with a merged architecture to generate both a segmented eye image and a quality estimation of the eye image. The segmented eye image can include a background region, a sclera region, an iris region, or a pupil region. In another aspect, a convolutional neural network with a merged architecture can be trained for eye image segmentation and image quality estimation. In yet another aspect, the device can use the segmented eye image to determine eye contours such as a pupil contour and an iris contour. The device can use the eye contours to create a polar image of the iris region for computing an iris code or biometric authentication. 120.-. (canceled)21. A method for training a convolutional neural network for eye image segmentation and image quality estimation , the method being performed by a system of one or more processors , and the method comprising:obtaining a training set of eye images;providing a convolutional neural network with the training set of eye images; andtraining the convolutional neural network with the training set of eye images,wherein the convolution neural network comprises a segmentation tower and a quality estimation tower, wherein the segmentation tower comprises segmentation layers and shared layers,wherein the quality estimation tower comprises quality estimation layers and the shared layers,wherein an output layer of the shared layers is connected to a first input layer of the segmentation tower and a second input layer of the segmentation tower,and wherein the output layer of the shared layers is connected to an input layer of the quality estimation layer.22. The method of claim 21 , wherein training the convolutional neural network with the training set of eye images comprises:processing an eye ...

Automated Measurement of Changes in Retinal, Retinal Pigment Epithelial, or Choroidal Disease

A method for for automatically measuring changes in retinal, retinal pigment epithelial, or choroidal disease includes retrieving a set of images of a fundus and selecting a plurality of images from the set of images. The plurality of images are co-registered and pre-processed such that the quality, contrast, and gain of each of the plurality of images is made similar. Then, a comparison is made between the plurality of images to determine a change in retinal, retinal pigment epithelial, or choroidal disease, wherein the change in retinal, retinal pigment epithelial, or choroidal disease is determined based on various disease metrics. Finally, an indication of the change in retinal, retinal pigment epithelial, or choroidal disease is generated for display to a user on a computing device. 1. A computer-implemented method for automatically measuring changes in retinal , retinal pigment epithelial , or choroidal disease , the method comprising:retrieving, with one or more processors, a set of images of a fundus;selecting, by the one or more processors, a plurality of images from the set of images, wherein the plurality of images includes images of the fundus captured at successive times; detecting a plurality of blood vessel locations within each of the plurality of images,', 'correlating the detected plurality of blood vessel locations in one of the plurality of images with a plurality of blood vessel locations in the remaining plurality of images, and', 'transforming the remaining plurality of images such that blood vessel locations in the remaining plurality of images are proximate to the detected plurality of blood vessel locations in the one of the plurality of images;, 'co-registering, by the one or more processors, the plurality of images, wherein co-registering the plurality of images includespre-processing, by the one or more processors, the plurality of images such that the quality, contrast, and gain of each of the plurality of images is made similar; ...

Gaze tracking variations using dynamic lighting position

Aspects of the present disclosure relate to eye tracking systems and methods which track eyes by illuminating the eyes using a light source and detecting the eye illuminations using a sensor. Implementations of the present disclosure may utilize a light source with a dynamic lighting position to account for changes in lighting conditions during the tracking which interfere with detection of the eye illuminations, such as reflections in glasses which may obscure a user's eyes.

METHOD AND A SYSTEM FOR EYE TRACKING

According to an aspect of the present inventive concept there is provided a method for eye tracking, comprising: capturing a sequence of digital images of an eye of a user; outputting data including said sequence of images to an image processing unit; processing said data by the image processing unit to determine a sequence of positions of the eye, each position being indicative of a gaze direction, acquiring biosignal data representing an activity of the eye; and in response to detecting closing of the eye based on the acquired biosignal data, pausing at least one of said capturing, said outputting and said processing. A system for implementing the method is also disclosed. 1. A method for eye tracking , comprising:capturing a sequence of digital images of an eye of a user;outputting data including said sequence of images to an image processing unit;processing said data by the image processing unit to determine a sequence of positions of the eye, each position being indicative of a gaze direction,acquiring biosignal data representing an activity of the eye; andin response to detecting closing of the eye based on the acquired biosignal data, pausing at least one of said capturing, said outputting and said processing.2. A method according to claim 1 , further comprising:returning to an active state each of said at least one of said capturing, said outputting and said processing being in a paused state.3. A method according to claim 2 , wherein said returning of an act to an active state includes transitioning said act from a paused state to a waiting state and transitioning said act from the waiting state to the active state.4. A method according to claim 2 , wherein said act of A method according to claim 2 , wherein said act of transitioning from the paused state to the waiting state is performed after a preset time delay from said act of pausing.5. A method according to claim 3 , wherein said transitioning from the waiting state to the active state is performed in ...

METHOD AND APPARATUS FOR AUTOMATED PLACEMENT OF SCANNED LASER CAPSULORHEXIS INCISIONS

Systems and methods are described for cataract intervention. In one embodiment a system comprises a laser source configured to produce a treatment beam comprising a plurality of laser pulses; an integrated optical system comprising an imaging assembly operatively coupled to a treatment laser delivery assembly such that they share at least one common optical element, the integrated optical system being configured to acquire image information pertinent to one or more targeted tissue structures and direct the treatment beam in a 3-dimensional pattern to cause breakdown in at least one of the targeted tissue structures; and a controller operatively coupled to the laser source and integrated optical system, and configured to adjust the laser beam and treatment pattern based upon the image information, and distinguish two or more anatomical structures of the eye based at least in part upon a robust least squares fit analysis of the image information. 115-. (canceled)16. A system for cataract surgery on an eye of a patient , comprising:a. a laser source configured to produce a treatment beam comprising a plurality of laser pulses;b. an integrated optical system comprising an Optical Coherence Tomographer (OCT) coupled to a treatment laser delivery assembly such that the OCT and the treatment laser delivery assembly share at least one common optical element, the integrated optical system being configured to acquire image information pertinent to one or more targeted tissue structures and direct the treatment beam in a 3-dimensional pattern to cause breakdown in at least one of the targeted tissue structures;c. a patient support configured to maintain the eye of the patient within a range of the optical system; and 1) adjust the laser beam and treatment pattern based upon the image information,', '2) operate the OCT to perform one or more A-scans of at least one anatomical structure of the eye at each of a plurality of XY locations, thereby obtaining image information of a ...

Ophthalmic image processing apparatus and ophthalmic imaging apparatus

An ophthalmic image processing apparatus of an embodiment includes a storage unit, a first brightness profile generation unit, a second brightness profile generation unit, and a brightness correction unit. The storage unit is configured to store image data acquired through scanning a subject's eye using optical coherence tomography. The first brightness profile generation unit is configured to generate a first brightness profile along a first direction by integrating brightness values of the image data. The second brightness profile generation unit is configured to process the first brightness profile to generate a second brightness profile. The brightness correction unit is configured to perform brightness correction of the image data based on the first brightness profile and the second brightness profile.

PREDICTING RESPONSE TO ANTI-VASCULAR ENDOTHELIAL GROWTH FACTOR THERAPY WITH COMPUTER-EXTRACTED MORPHOLOGY AND SPATIAL ARRANGEMENT FEATURES OF LEAKAGE PATTERNS ON BASELINE FLUORESCEIN ANGIOGRAPHY IN DIABETIC MACULAR EDEMA

Embodiments facilitate prediction of anti-vascular endothelial growth (anti-VEGF) therapy response in DME patients. A first set of embodiments discussed herein relates to training of a machine learning classifier to determine a prediction for response to anti-VEGF therapy based on a set of graph-network features and a set of morphological features generated based on FA images of tissue demonstrating DME. A second set of embodiments discussed herein relates to determination of a prediction of response to anti-VEGF therapy for a DME patient (e.g., non-rebounder vs. rebounder, response vs. non-response) based on a set of graph-network features and a set of morphological features generated based on FA imagery of the patient. 1. A non-transitory computer-readable storage device storing computer-executable instructions that when executed cause a processor to perform operations , the operations comprising:accessing a two-dimensional (2D) fluorescein angiography (FA) mage of a region of interest (ROI) demonstrating diabetic macular edema (DME), where the image is associated with a patient, where the image has a plurality of pixels, a pixel having an intensity;generating a leakage localization mask based on the FA image, where the leakage localization mask includes a plurality of leakage patches;generating a set of leakage graphs based on the leakage localization mask, where a node of a member of the set of leakage graphs is a member of the plurality of leakage patches;generating a set of graph-network features based on the set of leakage graphs;extracting a set of morphological features from the FA image based on the leakage localization mask;providing the set of graph-network features and the set of morphological features to a machine learning classifier configured to distinguish non-rebounders from rebounders in DME based on the set of graph-network features and the set of morphological features;receiving, from the machine learning classifier, a probability that the ...

COMPENSATING OPTICAL COHERENCE TOMOGRAPHY SCANS

A method of processing optical coherence tomography (OCT) scans, comprising: receiving OCT data comprising an OCT signal indicative of the level of scattering in a sample, the OCT data including the OCT signal for at least one scan through the sample, with the OCT signal having been measured at varying depth and position through the sample in each scan; processing the OCT data for each scan with depth to produce a indicative depth scan representative of the OCT signal at each depth through all of the scans; fitting a curve to the indicative depth scan, the curve comprising a first term which exponentially decays with respect to the depth and a second term which depends on the noise in the OCT signal; and calculating a compensated intensity for the OCT signal at each point through each scan, the compensated intensity comprising a ratio of a term comprising a logarithm of the OCT signal to a term comprising the logarithm of the fitted curve. 1. A method of processing optical coherence tomography (OCT) scans , comprising:receiving OCT data comprising an OCT signal indicative of the level of scattering in a sample, the OCT data including the OCT signal for at least one scan through the sample, with the OCT signal having been measured at varying depth and position through the sample in each scan;processing the OCT data for each scan with depth to produce an indicative depth scan representative of the OCT signal at each depth through all of the scans;fitting a curve to the indicative depth scan, the curve comprising a first term which exponentially decays with respect to the depth and a second term which depends on the noise in the OCT signal; andcalculating a compensated intensity for the OCT signal at each point through each scan, the compensated intensity comprising a ratio of a term comprising a logarithm of the OCT signal to a term comprising the logarithm of the fitted curve.2. The method of claim 1 , comprising generating an image in which each pixel of the image ...

IMAGE PROCESSING METHOD, PROGRAM, IMAGE PROCESSING DEVICE, AND OPHTHALMIC SYSTEM

An image processing method is provided. The image processing method includes: setting a first analysis point and a second analysis point on a fundus image so as to be symmetrical about a reference line; finding a first blood vessel running direction at the first analysis point and finding a second blood vessel running direction at the second analysis point; and comparing the first blood vessel running direction against the second blood vessel running direction. 128.-. (canceled)29. An image processing method comprising:setting a first analysis point and a second analysis point on a fundus image so as to be symmetrical about a reference line;computing a direction of a first blood vessel at the first analysis point;computing a direction of a second blood vessel at the second analysis point; andcomparing the first direction against the second direction.30. The image processing method of claim 29 , wherein comparison of the first direction against the second direction comprises analysis of asymmetry between a running direction of the first blood vessel and a running direction of the second blood vessel.31. The image processing method of claim 29 , wherein comparison of the first direction against the second direction is performed by quantifying asymmetry between a running direction of the first direction and a running direction of the second direction.32. The image processing method of claim 29 , wherein the fundus image is a choroidal vascular image.33. The image processing method of claim 29 , wherein the first direction and the second direction relate to running directions of the choroidal blood vessels.34. The image processing method of claim 29 , wherein the first direction is derived based on a brightness gradient of pixels in a first specific region containing the first analysis point claim 29 , and the second direction is derived based on a brightness gradient of pixels in a second specific region containing the second analysis point.35. The image processing ...

IMAGE PROCESSING METHOD, PROGRAM, AND IMAGE PROCESSING DEVICE

A first image is projective transformed into a reference image by using a projective transformation matrix on each pixel of the first image. A projective transformation matrix for transforming a tilted image n into a central image G is computed based on positions of combinations of twelve corresponding points indicated in a combination of the central image G with the tilted image n. The computed projective transformation matrix is then employed to perform a projective transformation of the tilted image n. A projective-transformed tilted image n is created thereby. 19.-.10. An image processing method comprising:specifying respective corresponding points in a reference image obtained by imaging a fundus with a first gaze and in a first image obtained by imaging the fundus with a second gaze which direction is different to direction of the first gaze;computing a projective transformation matrix based on the corresponding points; andemploying the projective transformation matrix to perform projection transformation of the first image.11. The image processing method of claim 10 , wherein the projective transformation matrix is a matrix for projective transformation so a position of each pixel in the first image is positioned at a position of a corresponding point in the reference image.12. The image processing method of claim 10 , wherein a reference projection point is identified as a reference point in the reference image projected onto the first image after the projective transformation.13. The image processing method of claim 10 , further comprising synthesizing the reference image together with the projective-transformed first image.14. The image processing method of claim 10 , wherein the corresponding points are a feature point of the fundus present in both the reference image and the first image.15. The image processing method of claim 10 , wherein the corresponding point is a branch point of a blood vessel of the fundus or an optic nerve head.16. The image ...

GLAUCOMA IMAGE RECOGNITION METHOD AND DEVICE AND DIAGNOSIS SYSTEM

The present disclosure provides a glaucoma image recognition method, device and diagnosis system. The method includes acquiring a fundus image; obtaining an optic disc image and an optic cup image according to the fundus image; obtaining a disc rim image according to the optic disc image and the optic cup image; and determining whether the fundus image is classified as glaucoma according to the disc rim image. 1. A method for recognizing glaucoma , the method comprising:acquiring a fundus image;obtaining, based on the fundus image, an optic disc image and an optic cup image;obtaining a disc rim image based on the optic disc image and the optic cup image; anddetermining, based on the disc rim image, whether the fundus image is classified as glaucoma or not.2. The method according to claim 1 , wherein the obtaining claim 1 , based on the fundus image claim 1 , an optic disc image and an optic cup image further comprises:detecting, using a first machine learning model, a valid region image including an optic disc from the fundus image, wherein a proportion of the optic disc occupied in the valid region image is greater than the proportion of the optic disc occupied in the fundus image;detecting, using a second machine learning model, the optic disc image from the valid region image; anddetecting, using a third machine learning model, the optic cup image from the valid region image.3. The method according to claim 2 , wherein the valid region image has a same color as the fundus image.4. The method according to claim 2 , wherein the second machine learning model outputs an optic disc binary image claim 2 , and the third machine learning model outputs an optic cup binary image.5. The method according to claim 4 , wherein the obtaining a disc rim image based on the optic disc image and the optic cup image comprises:subtracting the optic cup binary image from the optic disc binary image to obtain a disc rim binary image.6. The method according to claim 5 , wherein the ...

Vehicle lighting device and method of controlling luminance thereof

A vehicle lighting device and a method of controlling luminance thereof are provided. The vehicle lighting device includes a camera module configured to capture an image of the driver's face, a sensing unit configured to detect the surroundings of a vehicle, a lighting unit including at least one light source to illuminate the interior of the vehicle, and a controller. The controller is configured to acquire information on a daytime mode and a nighttime mode through the sensing unit, to acquire information on an infrared brightness level or information on the size of the pupil of the driver's eye based on the image of the driver's face captured by the camera module, and to control the luminance of the lighting unit in response to the acquired information.

IMAGE PROCESSING METHOD, PROGRAM, AND IMAGE PROCESSING DEVICE

Data is computed in order to visualize the velocity of blood fluid flowing through a blood vessel at a fundus. An image processing method includes a step of performing registration of each frame in a moving image configured by plural frames of an imaged fundus, and a step of computing visualization data enabling visualization of a state of blood fluid flowing through a blood vessel at the fundus based on a pixel value in each of the registered frames. 111.-. (canceled)12. An image processing method comprising:performing a first registration of a first fundus region in a plurality of a first frame in a first moving image of a subject eye;performing a second registration of a second fundus region in a plurality of a second frame in a second moving image of the subject eye;computing a first analysis data by performing an predetermined image processing of a first point in the first moving image after the first registration;computing a second analysis data by performing the predetermined image processing of a second point, which correspond to the first point, in the second moving image after the second registration; andcomparing the first analysis data and the second analysis data.13. The image processing method of claim 12 , wherein analyzing includes:computing first visualization data enabling visualization of a state of blood fluid flowing at the location including the first analysis point when imaging the first moving image; andcomputing second visualization data enabling visualization of a state of blood fluid flowing at the location including the second analysis point when imaging the second moving image.14. The image processing method of claim 13 , further comprising creating a comparative image to compare the first visualization data against the second visualization data.15. The image processing method of claim 13 , wherein:the first visualization data is computed based on a pixel value at the location including the first analysis point in each of the plurality ...

IMAGE PROCESSING METHOD, PROGRAM, AND IMAGE PROCESSING DEVICE

An image is created to visualize the efficacy of treatment to a fundus. 110.-. (canceled)11. An image processing method comprising:acquiring a first frame extracted from a first moving image that images a fundus of an examined eye;acquiring a second frame extracted from a second moving image that images a fundus of the examined eye in a timing different from a timing of the first moving image; andcomparing a first blood vessel displayed in the first frame and the second blood vessel displayed in the second frame.12. The image processing method of claim 11 , wherein comparing include comparison of a size of the first blood vessel and a size of the second blood vessel.13. The image processing method of claim 11 , further comprising performing positional alignment of the first frame and the second frame.14. The image processing method of claim 13 , wherein the performing positional alignment includes detecting corresponding points between the first frame and the second frame by template matching using cross correlation based on brightness values and aligning the detected corresponding points.15. The image processing method of claim 11 , further comprising:generating a synthesized image synthesizing the first frame and the second frame; andoutputting the synthesized image.16. The image processing method of claim 15 , wherein the generating the synthesized image includes:creating a first color image from the first frame;creating a second color image from the second frame wherein the second color is different from the first color; andsynthesizing the first color image and the second color image.17. The image processing method of claim 11 , wherein the displaying includes displaying the first frame and the second frame alternately at a specific time interval.18. The image processing method of claim 11 , wherein the displaying includes displaying the blood vessel in the first frame and the second frame in enlarged form.19. The image processing method of claim 18 , wherein ...

POST-PROCESSING METHOD TO IMPROVE LSO-BASED TRACKING IN OCT

After OCT scans are acquired, error compensation is be applied anew by identifying motion tracking data that was collected simultaneously with (or closest in time to) each acquired OCT scan. The effects of any previously applied motion tracking information is removed from an OCT scan before applying the new motion tracking data, which may provide higher resolution motion tracking. 1. A method for motion correction in an optical coherence tomography (OCT) system , comprising:collecting motion-tracking data associated with the eye of a patient, each collected motion-tracking datum having a respective motion-tracking sequence indicator;concurrent with the collecting of motion-tracking data, acquiring a plurality of OCT scans of the eye, each acquired OCT scan having a respective OCT scan sequence indicator;matching acquired OCT scans to collected motion-tracking data based on their respective OCT scan sequence indicator and motion-tracking sequence indicator; andcorrecting for displacement error in the acquired OCT scans based on their matched motion-tracking data; andstoring or displaying the displacement-corrected OCT scans.2. The method of claim 1 , wherein each of the acquired OCT scans consists of a plurality of A-scan at distinct locations claim 1 , and correcting for motion error in the acquired OCT scans based on their matched motion-tracking data claim 1 , includes:determining corrected locations of A-scans in the OCT scans based on their matched motion correction data, the corrected locations of A-scans constituting a point cloud of irregular point locations;transforming the point cloud into a uniform coordinate grid with A-scans at regularly ordered positions within the grid.3. The method of claim 2 , wherein transforming the point cloud into a uniform coordinate grid includes interpolating new A-scans at the regularly ordered positions based on the A-scans at irregular point locations within the point cloud.4. The method of claim 3 , wherein interpolating a ...

EYE-GAZE DETECTION SYSTEM, DISPLACEMENT DETECTION METHOD, AND DISPLACEMENT DETECTION PROGRAM

An eye-gaze detection system containing a mounting tool mounted on a user for use, includes: plural illumination units illuminating an eye of the user with invisible light; a camera capturing the eye on the basis of the invisible light; a pupil specifying unit specifying a pupil center of the user from a captured image having been captured; an obtaining unit obtaining information on a position of a center of a corneal curvature of the user on the basis of disposed positions of the illumination units and the camera, and illuminated positions by illumination light emitted from the illumination units to the eye; a vector specifying unit specifying a vector connecting the center of the corneal curvature and the pupil center on the captured image; and a displacement detection unit detecting displacement of a mounting state of the mounting tool mounted on the user on the basis of the vector. 1. An eye-gaze detection system containing a mounting tool mounted on a user for use , comprising:a plurality of illumination units configured to illuminate an eye of the user with invisible light;a camera configured to capture the eye of the user on the basis of the invisible light;a pupil specifying unit configured to specify a pupil center of the user from a captured image that has been captured by the camera;an obtaining unit configured to obtain information on a position of a center of a corneal curvature of the user on the basis of disposed positions of the plurality of illumination units, illuminated positions by illumination light emitted from the plurality of illumination units to the eye of the user, and a disposed position of the camera;a vector specifying unit configured to specify a vector connecting the center of the corneal curvature of the user and the pupil center on the captured image; anda displacement detection unit configured to detect displacement of a mounting state of the mounting tool mounted on the user on the basis of the vector.2. The eye-gaze detection ...

Method for the analysis of image data representing a three-dimensional volume of biological tissue

In the context of a method for the analysis of image data representing a three-dimensional volume ( 10, 20 ) of biological tissue, for each of a number of subvolumes at least two error probability values ( 41, 42, 43, 44 ) are generated, each of the values ( 41, 42, 43, 44 ) indicating a probability of a type of imaging error, the totality of subvolumes constituting the three-dimensional volume ( 10, 20 ). A single consolidated error probability value ( 51 ) is determined for each of the number of subvolumes, based on the at least two error probability values ( 41, 42, 43, 44 ). Subsequently, the image data is analyzed to obtain a physiologically relevant conclusion applying to a plurality of subvolumes, weighting in the analysis the image data of a given subvolume of the plurality of sub-volumes according to the consolidated error probability ( 51 ) of the subvolume.

METHOD FOR THE ANALYSIS OF IMAGE DATA REPRESENTING A THREE-DIMENSIONAL VOLUME OF BIOLOGICAL TISSUE

In the context of a method for the analysis of image data representing a three-dimensional volume of biological tissue, the image data comprises a first image representing the volume at a first point in time and a second image representing the volume at a second point in time being different from the first point in time. The method comprises the steps of: a) identifying a first subvolume of the volume represented by the first image having a major extension in a predefined direction and a second subvolume of the volume represented by the second image having a major extension in the predefined direction, whereas the first subvolume and the second subvolume represent a same region of the three-dimensional volume; b) creating a distance matrix from image data of a succession of voxels of the first subvolume in the predefined direction and image data of a succession of voxels of the second subvolume in the predefined direction; and c) analyzing the distance matrix to obtain at least one local measure for a probability of growth of a layer of the biological tissue represented by the first and the second subvolume, along the predefined direction. 1. A method for the analysis of image data representing a three-dimensional volume of biological tissue , the image data comprising a first image representing the volume at a first point in time and a second image representing the volume at a second point in time being different from the first point in time , the method comprising the steps of:a) identifying a first subvolume of the volume represented by the first image having a major extension in a predefined direction and a second subvolume of the volume represented by the second image having a major extension in the predefined direction, whereas the first subvolume and the second subvolume represent a same region of the three-dimensional volume;b) creating a distance matrix from image data of a succession of voxels of the first subvolume in the predefined direction and image ...

Automated separation of binary overlapping trees

Provided are systems and methods for analyzing images. An exemplary method can comprise receiving at least one image having one or more annotations indicating a feature. The method can comprise generating training images from the at least one image. Each training image can be based on a respective section of the at least one image. The training images can comprise positive images having the feature and negative images without the feature. The method can comprise generating a feature space based on the positive images and the negative images. The method can further comprise identifying the feature in one or more unclassified images based upon the feature space.

SYSTEMS AND METHODS FOR ANATOMY-CONSTRAINED GAZE ESTIMATION

The disclosure relates to systems, methods and programs for anatomically-constrained gaze estimation. More specifically, the disclosure is directed to systems, methods and programs for providing a point of reference (PoR) in a 3D field and/or 2D plane, based on 6 DOF head pose constrained by the eyeball center being fixed in a common 3D coordinate system. 1. A system for providing user-specific gaze estimation , the system comprising:a. an imaging module including an optical sensor;b. a graphic processing module (GPM);{'claim-text': ["i. capture an image of a subject's face via the imaging module;", 'ii. extract a plurality of features from the captured image;', "iii. determine the subject's head pose in a predetermined Cartesian coordinate system based at least in part on the plurality of features;", "iv. unproject the subject's irises from a portion of the plurality of features into the predetermined Cartesian coordinate system, forming right and left unprojected three-dimensional (3D) iris contours; and", 'v. using each of the right and left unprojected three-dimensional (3D) iris contours, determine at least one of eye location, gaze direction, or point of regard (PoR), wherein an eyeball center is fixed in the predetermined Cartesian coordinate system.'], '#text': 'c. a central processing module (CPM) including at least one processor in communication with the imaging module, the GPM, and a memory having thereon a processor-readable medium and a set of executable instructions that when executed cause the at least one processor to:'}2. The system of claim 1 , further comprising instructions operable to cause the at least one processor to perform a calibration to measure user-specific eye parameter.3. The system of claim 2 , wherein the calibration comprises determining at least one of: the relative position and orientation of a display with respect to the optical sensor or at least one intrinsic parameter of the optical sensor.4. The system of claim 3 , wherein ...

MEDICAL IMAGING APPARATUS AND METHOD FOR THE IMAGING OF A LIGHT-SENSITIVE OBJECT, SUCH AS BIOLOGICAL TISSUE

A medical imaging apparatus () and method for imaging a light-sensitive object (), such as tissue () of the eye (), displays the object () in spectral bands () of the visible light range () in which the object is sensitive and cannot be illuminated. The apparatus () has a camera () for capturing input images () in which a spectral signature () of the object is represented by an input set () of spectral bands (). The apparatus generates output images () in which the spectral signature () in the visible light range () is represented by an output set () of spectral bands (). Replacing at least one input-only spectral band () in the input set () by at least one output-only spectral band () in the output set () enables capture of input images () in spectral bands () where the object () has less sensitivity, such as in the non-visible light-range (), and display of the object () in spectral bands () where the object would be too sensitive for illumination (). 1123361. A medical imaging apparatus () for the imaging of a light-sensitive object () , such as biological tissue () , the object having a spectral signature () , the medical imaging apparatus () comprising:{'b': 8', '10', '36', '2', '15', '16, 'a camera () for capturing input images (), the spectral signature () of the object () being represented in the input images by an input set () of spectral bands (),'}{'b': 20', '22, 'an output interface () for transmitting output images (),'}{'b': 22', '60', '37', '29', '30, 'wherein, in the output images (), the spectral signature () in the visible light range () is represented by an output set () of spectral bands (),'}{'b': 38', '15', '39', '29, 'wherein at least one input-only spectral band () in the input set () is replaced by at least one output-only spectral band () in the output set (),'}{'b': '1', 'the medical imaging apparatus () further comprising{'b': 54', '56', '15', '29, 'a storage member (), in which calibration data () are stored for mapping the input set () ...